Location: Middlesex (3 days onsite, 2 days from home)
Salary: Negotiable depending on experience
Job Ref: J13078

A market leading global logistics organisation is seeking a highly motivated Airline Capacity Planning Data Scientist who wants to apply their work in a real, high impact environment.
Your work will directly influence how capacity is planned, optimised, and delivered within a complex, high volume operational setting.

This role sits at the intersection of data science and operations research, with a strong focus on simulation, modelling, and real world system optimisation.
You will work with large scale datasets to build machine learning models and develop advanced simulation tools that support critical planning decisions.

The role:
Design and build machine learning models to forecast demand, utilisation and system performance
Work with large scale, time series datasets to engineer features and improve model accuracy
Apply robust validation, tuning and model selection techniques to deliver reliable outputs
Build and calibrate discrete event simulation (DES) models of complex operational systems to stress test capacity under different demand scenarios
Carry out scenario analysis and what if modelling to support planning and investment decisions
Translate complex analytical outputs into clear, actionable insights for operational stakeholders
Develop tools and dashboards to monitor system performance and support decision making
Work closely with operational teams to ensure models reflect real world constraints and behaviours

Experience required:
Master’s degree (or equivalent) in Data Science, Statistics, Operations Research, Computer Science, Mathematics, or a closely related quantitative discipline
Strong experience in a Data Scientist or Operational Research focused role working with large, complex datasets
Solid understanding of machine learning techniques such as gradient boosting, random forests and time series modelling
Experience building and deploying models used in real world decision making (e.g. ensemble methods, regularised regression)
Advanced proficiency in R, including tidyverse, data.table, caret or tidymodels, xgboost and Shiny
Strong SQL skills with experience querying large scale relational databases such as Azure SQL or PostgreSQL
Experience working with high volume or time based data, including feature engineering
Experience with simulation, discrete event simulation, or operations research techniques is highly desirable
Ability to communicate complex analysis clearly to non-technical stakeholders
Comfortable working in fast paced, operational environments
Proactive, hands on approach with the ability to take ownership of problems end to end

If you want to work on complex systems where your output is actually used and matters, this is a genuinely strong opportunity to do that.

Please note we can only accept applications from those with current and full UK working rights for this role, as sponsorship is not available.

If this sounds like the role for you then please apply today.

Alternatively, you can refer a friend or colleague through our referral scheme. For each successful placement, you will be eligible for our reward scheme with no limit on referrals.
Datatech is one of the UK’s leading recruitment agencies in analytics and the host of the Women in Data event. For more information, visit (url removed)

We believe in better. And we make it happen.

Better content. Better products. And better careers.

Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate.

We turn big ideas into the products, content and services millions of people love.

And we do it all right here at Sky.

What you’ll do
We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform.

• Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis.
• Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets.
• Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance.
• Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement.
• Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs.
• Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems.

What you’ll bring

• Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance.
• Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). .
• Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe).
• Experience with high-volume data processing and real-time streaming architectures.
• Strong understanding of recommendation system design and personalisation algorithms.
• Familiarity with Generative AI and its applications in production settings.
• Exceptional communication and analytical problem-solving skills.
• Proven successful experience in mentoring less experienced engineers to improve their technical skills

A Typical Day at the Office

When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what’s happening in the tech communities, then catch up with everyone at the team stand-up. After that, you’ll join your team and pick the first task to get cracking on.

At lunchtime, you’ve got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you’re back, you’ll carry on working with your team on your current feature.

Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective.

Global OTT Technology

Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world’s best entertainment, news and sport.

The rewards

There’s one thing people can’t stop talking about when it comes to : the perks. Here’s a taster:

• Sky Q, for the TV you love all in one place
• The magic of Sky Glass at an exclusive rate
• A generous pension package
• Private healthcare
• Discounted mobile and broadband
• A wide range of Sky VIP rewards and experiences

Inclusion & how you’ll work

We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can.

We’ve embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You’ll find out more about what hybrid working looks like for your role later on in the recruitment process.

Your office space

Osterley

Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers.

On campus, you’ll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon.

We’d love to hear from you

Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It’s a place where you can explore what if, how far, and what next.

But better doesn’t stop at what we do, it’s how we do it, too. We embrace each other’s differences. We support our community and contribute to a sustainable future for our business and the planet.

If you believe in better, we’ll back you all the way.
Just so you know: if your application is successful, we’ll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.

We believe in better. And we make it happen.

Better content. Better products. And better careers.

Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate.

We turn big ideas into the products, content and services millions of people love.

And we do it all right here at Sky.

What you’ll do
We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform.

• Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis.
• Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets.
• Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance.
• Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement.
• Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs.
• Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems.

What you’ll bring

• Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance.
• Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). .
• Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe).
• Experience with high-volume data processing and real-time streaming architectures.
• Strong understanding of recommendation system design and personalisation algorithms.
• Familiarity with Generative AI and its applications in production settings.
• Exceptional communication and analytical problem-solving skills.
• Proven successful experience in mentoring less experienced engineers to improve their technical skills

A Typical Day at the Office

When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what’s happening in the tech communities, then catch up with everyone at the team stand-up. After that, you’ll join your team and pick the first task to get cracking on.

At lunchtime, you’ve got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you’re back, you’ll carry on working with your team on your current feature.

Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective.

Global OTT Technology

Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world’s best entertainment, news and sport.

The rewards

There’s one thing people can’t stop talking about when it comes to : the perks. Here’s a taster:

• Sky Q, for the TV you love all in one place
• The magic of Sky Glass at an exclusive rate
• A generous pension package
• Private healthcare
• Discounted mobile and broadband
• A wide range of Sky VIP rewards and experiences

Inclusion & how you’ll work

We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can.

We’ve embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You’ll find out more about what hybrid working looks like for your role later on in the recruitment process.

Your office space

Osterley

Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers.

On campus, you’ll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon.

We’d love to hear from you

Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It’s a place where you can explore what if, how far, and what next.

But better doesn’t stop at what we do, it’s how we do it, too. We embrace each other’s differences. We support our community and contribute to a sustainable future for our business and the planet.

If you believe in better, we’ll back you all the way.
Just so you know: if your application is successful, we’ll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.

We believe in better. And we make it happen.

Better content. Better products. And better careers.

Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate.

We turn big ideas into the products, content and services millions of people love.

And we do it all right here at Sky.

What you’ll do
We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform.

• Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis.
• Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets.
• Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance.
• Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement.
• Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs.
• Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems.

What you’ll bring

• Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance.
• Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). .
• Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe).
• Experience with high-volume data processing and real-time streaming architectures.
• Strong understanding of recommendation system design and personalisation algorithms.
• Familiarity with Generative AI and its applications in production settings.
• Exceptional communication and analytical problem-solving skills.
• Proven successful experience in mentoring less experienced engineers to improve their technical skills

A Typical Day at the Office

When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what’s happening in the tech communities, then catch up with everyone at the team stand-up. After that, you’ll join your team and pick the first task to get cracking on.

At lunchtime, you’ve got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you’re back, you’ll carry on working with your team on your current feature.

Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective.

Global OTT Technology

Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world’s best entertainment, news and sport.

The rewards

There’s one thing people can’t stop talking about when it comes to #LifeAtSky: the perks. Here’s a taster:

• Sky Q, for the TV you love all in one place
• The magic of Sky Glass at an exclusive rate
• A generous pension package
• Private healthcare
• Discounted mobile and broadband
• A wide range of Sky VIP rewards and experiences

Inclusion & how you’ll work

We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can.

We’ve embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You’ll find out more about what hybrid working looks like for your role later on in the recruitment process.

Your office space

Osterley

Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers.

On campus, you’ll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon.

We’d love to hear from you

Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It’s a place where you can explore what if, how far, and what next.

But better doesn’t stop at what we do, it’s how we do it, too. We embrace each other’s differences. We support our community and contribute to a sustainable future for our business and the planet.

If you believe in better, we’ll back you all the way.
Just so you know: if your application is successful, we’ll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.

We believe in better. And we make it happen.

Better content. Better products. And better careers.

Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate.

We turn big ideas into the products, content and services millions of people love.

And we do it all right here at Sky.

What you’ll do
We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform.

• Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis.
• Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets.
• Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance.
• Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement.
• Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs.
• Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems.

What you’ll bring

• Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance.
• Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). .
• Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe).
• Experience with high-volume data processing and real-time streaming architectures.
• Strong understanding of recommendation system design and personalisation algorithms.
• Familiarity with Generative AI and its applications in production settings.
• Exceptional communication and analytical problem-solving skills.
• Proven successful experience in mentoring less experienced engineers to improve their technical skills

A Typical Day at the Office

When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what’s happening in the tech communities, then catch up with everyone at the team stand-up. After that, you’ll join your team and pick the first task to get cracking on.

At lunchtime, you’ve got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you’re back, you’ll carry on working with your team on your current feature.

Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective.

Global OTT Technology

Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world’s best entertainment, news and sport.

The rewards

There’s one thing people can’t stop talking about when it comes to : the perks. Here’s a taster:

• Sky Q, for the TV you love all in one place
• The magic of Sky Glass at an exclusive rate
• A generous pension package
• Private healthcare
• Discounted mobile and broadband
• A wide range of Sky VIP rewards and experiences

Inclusion & how you’ll work

We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can.

We’ve embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You’ll find out more about what hybrid working looks like for your role later on in the recruitment process.

Your office space

Osterley

Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers.

On campus, you’ll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon.

We’d love to hear from you

Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It’s a place where you can explore what if, how far, and what next.

But better doesn’t stop at what we do, it’s how we do it, too. We embrace each other’s differences. We support our community and contribute to a sustainable future for our business and the planet.

If you believe in better, we’ll back you all the way.
Just so you know: if your application is successful, we’ll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.

We believe in better. And we make it happen.

Better content. Better products. And better careers.

Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate.

We turn big ideas into the products, content and services millions of people love.

And we do it all right here at Sky.

What you’ll do
We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform.

• Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis.
• Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets.
• Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance.
• Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement.
• Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs.
• Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems.

What you’ll bring

• Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance.
• Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). .
• Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe).
• Experience with high-volume data processing and real-time streaming architectures.
• Strong understanding of recommendation system design and personalisation algorithms.
• Familiarity with Generative AI and its applications in production settings.
• Exceptional communication and analytical problem-solving skills.
• Proven successful experience in mentoring less experienced engineers to improve their technical skills

A Typical Day at the Office

When you come in, you can grab a coffee or a bit of breakfast from one of the many (subsidised) cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what’s happening in the tech communities, then catch up with everyone at the team stand-up. After that, you’ll join your team and pick the first task to get cracking on.

At lunchtime, you’ve got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you’re back, you’ll carry on working with your team on your current feature.

Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective.

Global OTT Technology

Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world’s best entertainment, news and sport.

The rewards

There’s one thing people can’t stop talking about when it comes to : the perks. Here’s a taster:

• Sky Q, for the TV you love all in one place
• The magic of Sky Glass at an exclusive rate
• A generous pension package
• Private healthcare
• Discounted mobile and broadband
• A wide range of Sky VIP rewards and experiences

Inclusion & how you’ll work

We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can.

We’ve embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You’ll find out more about what hybrid working looks like for your role later on in the recruitment process.

Your office space

Osterley

Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers.

On campus, you’ll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon.

We’d love to hear from you

Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It’s a place where you can explore what if, how far, and what next.

But better doesn’t stop at what we do, it’s how we do it, too. We embrace each other’s differences. We support our community and contribute to a sustainable future for our business and the planet.

If you believe in better, we’ll back you all the way.
Just so you know: if your application is successful, we’ll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.

Principal Software Engineer – AI & Innovation

Recruiting a Principal Software Engineer with a proven track record of delivering innovative, AI driven solutions and the curiosity to explore beyond traditional technology boundaries.

Within the newly createdAI & Innovation team, you will shape the future of the organisation’s products through cutting-edge technology, experimentation and creative thinking.

A truly exciting opportunity to influence and create something new.

Key Responsibilities

Build innovative MVPs to validate ideas and accelerate learning

Lead the design and implementation of scalable, high-performance software systems

Collaborate closely with Product, Design, QA, and Engineering teams

Evaluate, experiment and recommend new technologies, frameworks and tools

Mentor and coach engineers to create a culture of innovation and continuous improvement

Oversee code reviews and ensure delivery of high-quality maintainable software

Troubleshoot and resolve complex technical challenges

Contribute to strategic planning and align technology decisions with business goals

Essential Skills

Significant experience in a senior software engineering position

Proven experience delivering innovative AI solutions

Practical knowledge of AI and recommend tools to best suit the needs

Strong understanding of microservices and modern web architectures

Deep expertise in programming languages and frameworks

Extensive experience designing large-scale systems

Strong knowledge of AWS cloud architecture and services

Excellent problem-solving skills and a results-driven mindset

Experience mentoring and guiding technical teams to deliver

Desirable Experience

DevOps practices and CI/CD pipelines

Secure-by-design development and security best practices

Contributions to open-source projects

TPBN1_UKTJ

White Collar Factory (95009), United Kingdom, London, LondonEngineering Manager – Software & MLAbout this role

We are looking for a Software Engineering Manager who brings a solid foundation in modern development and some experience with Machine Learning environments. You’ll lead and grow a team that builds the core software powering our data-driven financial products, ensuring our models are integrated into seamless, consumer-facing experiences.

What you’ll do

• Lead & Scale: Support a cross-functional group of engineers to design, develop, and integrate software features that are vital to the lives of credit card consumers.
• Nurture Talent: Coach and nurture your engineers, including those working on ML integration to achieve their technical, business, and personal goals.
• Bridge the Gap: Collaborate with Product Managers and Data Scientists to ensure ML models are effectively integrated into our production software.
• Build Robust Systems: Oversee the development of platforms that are performant, secure, and capable of handling the unique deployment needs of AI-powered features.
• Optimize Delivery: Enhance engineering and agile processes, ensuring that model updates and software releases move in sync.

What we’re looking for

• Leadership Excellence: Proven experience leading and supporting software engineering teams to achieve business goals.
• Technical Breadth: Excellent knowledge of RESTful API development in modern languages (Java, Python, or .Net) and experience with Cloud environments (AWS or Azure).
• AI Awareness: You aren’t necessarily a researcher, but you have expectations of how AI fits into the stack. You understand the basics of model inference, data requirements, and how to manage the non-deterministic nature of AI.
• Strategic Thinking: Comfortable making technical trade-offs between the need for rapid experimentation and long-term architectural stability.
• Collaborative Mindset: Ability to communicate effectively across engineering teams to maximize inner-sourcing and reduce technical debt.

What you’ll get to learn

• ML Integration at Scale: How to take machine learning models out of the lab and into a high-concurrency production environment.
• Regulated AI: Navigating the complexities of fairness and transparency in a regulated financial landscape.
• Cloud Evolution: Deepening your expertise in AWS/Cloud native tools that support modern intelligent applications.

Where and how you’ll work

This is a permanent position based in either our London or Nottingham offices.

We have a hybrid working model. You’ll be based in the office 3 days a week (Tuesdays, Wednesdays, and Thursdays) to foster team connection and collaboration.

What’s in it for you

• Innovation Time: We give you 10% of your time to work on cutting-edge projects—whether that’s exploring new AI frameworks or building internal tools.
• Growth: Access to Capital One University and external training to help you grow as both a leader and a technical strategist.
• Total Reward: Competitive salary, performance bonus, and immediate access to core benefits (pension, private medical, and generous holiday).
• World-Class Facilities: From our Nottingham gym and music rooms to our London rooftop running track and premium coffee bars.

Our Commitment to Diversity

We pride ourselves on hiring the best people, not the same people. We partner with organisations like Women in Tech and Stonewall to ensure we build teams that reflect the customers we serve. We offer a host of internal networks including REACH (Race Equality and Culture Heritage), OutFront (LGBTQ+ support), and Mind Your Mind.

Capital One is committed to diversity in the workplace.

If you require a reasonable adjustment, please contact ukrecruitment@capitalone.com All information will be kept confidential and will only be used for the purpose of applying a reasonable adjustment.

For technical support or questions about Capital One’s recruiting process, please send an email to Careers@capitalone.com

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Who We Are

At Capital One, we’re building a leading information-based technology company. Still founder-led by Chairman and Chief Executive Officer Richard Fairbank, Capital One is on a mission to help our customers succeed by bringing ingenuity, simplicity, and humanity to banking. We measure our efforts by the success our customers enjoy and the advocacy they exhibit. We are succeeding because they are succeeding.

Guided by our shared values, we thrive in an environment where collaboration and openness are valued. We believe that innovation is powered by perspective and that teamwork and respect for each other lead to superior results. We elevate each other and obsess about doing the right thing. Our associates serve with humility and a deep respect for their responsibility in helping our customers achieve their goals and realize their dreams. Together, we are on a quest to change banking for good.

Our client is an established buy-side Market Maker & Liquidity provider. Strong business performance means that they are actively expanding their headcount. As a consequence the opportunity has arisen for an experienced KDB Developer to work alongside their Quants and Traders. This is an exciting opportunity to take ownership of critical data and analytics capabilities in a business where your work will directly support front-office decision-making, research, and platform performance.

In addition to the base salary the firm also pays exceptional performance related cash bonuses every 6 months.

THE ROLE: KDB Developer

This position sits within a small, highly capable team focused on building, improving and supporting the firms data environment. The successful candidate will play a key role in designing and developing scalable data collection and analytics solutions, while helping ensure the platform remains robust, efficient and fit for front-office use.

You will work closely with trading and quantitative teams to deliver high-quality data pipelines, analytics tooling and monitoring solutions. The role covers the full development lifecycle, from early-stage investigation and prototyping through to implementation, testing, release and ongoing support. It offers the chance to work on real-time data challenges in a commercially important environment where performance, reliability and insight generation are central.

KEY RESPONSIBILITIES:

• Work closely with traders and quants to deliver practical solutions aligned to business needs
• Build and enhance analytics capabilities that improve visibility and insight for front-office and management teams
• Develop data ingestion pipelines to capture, organise and store high-volume internal and external data
• Create and improve frameworks that support real-time dashboards, execution analysis and market microstructure research
• Design and implement CEP processes to identify anomalies and generate actionable signals
• Maintain, troubleshoot and strengthen the stability, performance and cost-efficiency of the platform
• Contribute across the full software delivery lifecycle, including research, testing, deployment and production support

SKILLS / EXPERIENCE REQUIRED: KDB+ Developer

• 5+ years experience in data or analytics development
• Strong hands-on expertise with KDB+/q
• Solid background in Linux systems engineering, including lower-level networking and kernel knowledge
• Experience working with large-scale storage, data distribution and recovery mechanisms
• Knowledge of AWS services and Kubernetes configuration
• Experience in big data optimisation, analytics and visualisation
• Familiarity with continuous integration practices

AI GTM Solution Engineer (GenAI / LLM / Pre-Sales)

Were hiring an AI GTM Solution Engineer to help shape and deliver cutting-edge Generative AI (GenAI) and LLM-powered solutions for enterprise customers.

This is a customer-facing pre-sales / solution engineering role where youll design, prototype and demonstrate AI solutions, working closely with sales, product and engineering teams.

Key Responsibilities

• Design and deliver AI / GenAI solutions aligned to customer use cases
• Build and showcase POCs, demos and technical presentations
• Work with LLMs, LangChain, OpenAI APIs and AI agents
• Support solution architecture, APIs, integrations and cloud deployments
• Collaborate across GTM, sales and engineering to refine offerings

Requirements

• Experience in Solution Engineering, Pre-Sales, Sales Engineering or Technical Consulting
• Strong knowledge of LLMs, Generative AI, Machine Learning
• Hands-on with LangChain, OpenAI, GPT or similar tools
• Programming experience in Python
• Experience with APIs, integrations and REST services
• Cloud exposure: AWS, Azure or GCP
• Proven experience delivering POCs, demos or customer-facing solutions

Desirable

• Experience building AI-powered enterprise solutions
• Background in startups or high-growth environments
• Exposure to AI agents or agentic workflows

This is a high-impact opportunity to work at the forefront of AI innovation, influencing GTM strategy and delivering real-world AI solutions.

Founding Engineer (Python, LLMs, TypeScript) Salary up to £250k + Equity London based onsite
Build the Future of AI Voice
Top VC backed Series A Startup, building AI voice agents that transform how trades businesses operate, from handling customer interactions to streamlining operations at scale.

As a founding engineer, you won’t just ship features; you’ll shape the product, define the architecture, and play a key role in how AI interacts with real-world customers every day. Roles like this are rare: high ownership, direct customer impact, and the chance to build something foundational from the ground up, a hallmark of early-stage AI startup.
What You’ll Do

• Build and ship core product features across a modern stack (Python, TypeScript, cloud, event-driven systems)
• Own problems end-to-end from customer discovery through to production deployment
• Work directly with users to turn messy, real-world workflows into elegant AI-powered solutions
• Balance speed vs scalability, knowing when to prototype and when to harden systems
• Set the standard for engineering excellence across reliability, testing, and security

What You Bring
Experience

• 5-10 years in full-stack engineering (backend-leaning)
• Proven track record building and shipping AI products end-to-end — especially agentic systems
• Experience in early-stage startups (or founder-level ownership mindset)
• Bonus: direct experience working with customers

Technical

• Strong Python or TypeScript skills (async Python is essential)

• Hands-on experience with LLMs and modern AI tooling

• Deep understanding of:

• async/await, coroutines

• httpx, AsyncOpenAI

• production-grade error handling in async systems

Experience with cloud infrastructure (Kubernetes, serverless, distributed systems) Mindset

• You move fast and take ownership
• You’re comfortable with ambiguity and building from first principles
• You care about shipping real products — not just prototypes

If you’re excited by the idea of building foundational AI products from scratch, and want your work to directly shape what gets built, this is that opportunity!

AI consultancy building capabilities in decision intelligence, semantic data systems and operational AI. This role leads the capability that transforms data and models into real operational decisions and measurable business outcomes.

Combining decision architecture, applied modelling and AI system integration, ensuring analytical work directly drives how organisations plan, price, forecast and operate. You will lead complex client engagements, shape the firm’s decision science practice, working alongside AI engineering and consulting leaders to design, deliver and scale production decision systems.

What you will do

Client leadership - Lead high-value engagements in decision intelligence and AI-enabled operations, working directly with C-suite, data leaders, and operational heads. Translate complex business problems into decision systems with measurable outcomes across areas such as pricing optimisation, demand forecasting, risk and fraud modelling, resource allocation, and AI-enabled decision systems.

Build capability - Define and scale the firm’s Decision Science practice. Create modelling frameworks, reusable components, and decision accelerators. Shape how modelling integrates with ontologies, semantic data platforms, and AI agents.

Design decision systems - Go beyond modelling to architect end-to-end decision systems combining data pipelines, ML models, business rules, semantic layers and AI agents, all Embedded in real workflows and operational systems.

Grow the business - Drive new client relationships and expand existing accounts through measurable value creation. Lead proposals, shape thought leadership and build market visibility in decision intelligence.

Lead the team - Mentor Decision Scientists and AI engineers. Set hiring standards, build delivery playbooks and contribute to a culture of high-agency, high-accountability builders.

What we are looking for

• 8+ years in decision science, data science, quantitative modelling, or operations research.
• Proven track record applying models in live business decision environments.
• Strong fluency in Python, modern ML tools, and decision optimisation frameworks.
• Deep understanding of statistical modelling and machine learning with experience deploying models into production-scale systems.

Beneficial: pricing and revenue optimisation, forecasting and supply chain, risk and fraud modelling, reinforcement learning, causal inference and experimentation.

Experience with AI systems, agentic architectures, or decision intelligence platforms is a strong advantage, as is consulting or senior client leadership experience.

AI Engineer Placement Programme- No Experience Needed Future-proof your career in Artificial Intelligence - starting today. Looking for a career change? Currently employed but want something better? Or maybe you're between jobs and ready for a fresh start? Their AI Placement Programme is designed to get you into one of the fastest-growing industries with zero experience required. Train online at your own pace and land your first AI Engineer role in 1-3 months. Please note this is a training course and fees apply Job guaranteed - complete the programme and get a job or get your money back. Candidates earn £28,000-£45,000. How It Works Step 1 - AI Engineering Fundamentals Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 - Data Fundamentals Understand the data workflow, from collection to cleaning, and learn how to prepare data for AI applications. Step 3 - Notebooks & IDEs Get hands-on with industry-standard tools like Jupyter Notebooks and VS Code to develop AI systems. Step 4 - Python Programming Master Python, covering everything from the basics to object-oriented programming (OOP). Step 5 - Python Streamlit Project Apply your Python skills by building a car price prediction app using Python and Streamlit. Step 6 - Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 - AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using real-world AI techniques. Step 8 - AI Prompt Engineering Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 - Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems using RAG techniques and vector databases. Step 10 - AI Specialised Customer Service Chatbot Project Combine prompt engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 - Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 - Machine Learning Project Put your machine learning knowledge into practice with a hands-on project. Step 13 - AI & Data Ethics Study the ethical considerations in AI, including issues of bias, fairness, and data privacy. Step 14 - Oral Exam Complete a virtual oral exam to assess your understanding and ability to apply your learning. Step 15 - AWS Certified Cloud Practitioner Finish with the AWS Certified Cloud Practitioner course and exam to gain essential cloud computing knowledge. They Get You Hired They 're not new to this. The company has 15+ years of experience and has placed over 5,000 people into new roles. Their job programmes include certified tutors, UK-accredited qualifications, and one-on-one support from a recruitment adviser focused on placing you. They don't believe in empty promises. Complete their programme, follow the process, and if you don't land a job, you get your money back. "Five months from complete beginner to AI engineer. Best decision I ever made." - Jamie W., now working as a Junior AI Engineer in London Ready to Start? If you're motivated, curious, and excited about technology, they'll help you turn that into a career you can be proud of. Apply now, and one of thier expert Career Advisors will be in touch within 4 working hours to guide you through your next steps.

Machine Learning | Deep Learning | Time Series | Climate | Remote Sensing | PyTorch | scikit‑learn | Geospatial | AWS | MLOps | Python | Risk Modelling | FinTech | Do you want to work with a business building AI‑native data system that bring clarity and credibility to nature‑based assets? A business tackling complex, real‑world environmental challenges, helping organisations make high‑impact decisions around risk, resilience and commercial performance? This is the chance to join as a Machine Learning Engineer working with a climate‑tech scale‑up applying cutting‑edge Machine Learning to satellite data, weather models and environmental signals, reshaping how nature is valued in real‑world decision‑making. Joining their AI team, you’ll design and deploy models that forecast climate volatility, detect vegetation stress, and generate risk‑driven insights from remote sensing and time‑series data. You’ll work across AI, climate science, geospatial modelling and scalable pipelines, contributing meaningfully from day one. What you’ll be working on: • Building and evaluating Machine Learning/DL models for satellite, weather and climate data • Forecasting environmental and risk‑related signals (volatility, vegetation stress, land‑surface change) • Developing geospatial and remote‑sensing models (Sentinel‑1/2, GEDI, optical, radar, LiDAR) • Creating time‑series and forecasting models for environmental change • Translating business questions into robust modelling problems • Turning research prototypes into scalable, reproducible AI pipelines • Communicating assumptions, uncertainty and results clearly The must‑haves: • Strong background in Machine Learning, DL and Applied Statistics • Time‑series modelling + backtesting • Experience with geospatial and climate datasets • Python stack: PyTorch, scikit‑learn, scipy • Reproducible workflows (Git, AWS/cloud, W&B) Nice‑to‑haves: • Risk modelling, financial time series, portfolio optimisation (great for FinTech/quant backgrounds) • Climate/weather datasets (CMIP, forecast data) • Geospatial tools: rasterio, xarray, geopandas, GDAL • Remote sensing (optical, radar, LiDAR) • MLOps: CI/CD, containerisation, monitoring • Startup or fast‑paced product environment The role offers £110k–£130k, a global team environment, and the chance to shape the future of AI‑powered environmental and risk intelligence. If it ticks those boxes, don’t hang about message me: (url removed) Machine Learning | Deep Learning | Time Series | Climate | Remote Sensing | PyTorch | scikit‑learn | Geospatial | AWS | MLOps | Python | Risk Modelling | FinTech

Trainee AI Engineer - No Experience Needed Future-proof your career in Artificial Intelligence - starting today. Looking for a career change? Currently employed but want something better? Or maybe you're between jobs and ready for a fresh start? Their AI Traineeship is designed to get you into one of the fastest-growing industries with zero experience required. Train online at your own pace and land your first AI Engineer role in 1-3 months. Please note this is a training course and fees apply Job guaranteed - complete the programme and get a job or get your money back. Candidates earn £28,000-£45,000. How It Works Step 1 - AI Engineering Fundamentals Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 - Data Fundamentals Understand the data workflow, from collection to cleaning, and learn how to prepare data for AI applications. Step 3 - Notebooks & IDEs Get hands-on with industry-standard tools like Jupyter Notebooks and VS Code to develop AI systems. Step 4 - Python Programming Master Python, covering everything from the basics to object-oriented programming (OOP). Step 5 - Python Streamlit Project Apply your Python skills by building a car price prediction app using Python and Streamlit. Step 6 - Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 - AI Sentiment Analysis Projecti Work with Hugging Face to build a sentiment analysis classifier using real-world AI techniques. Step 8 - AI Prompt Engineering Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 - Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems using RAG techniques and vector databases. Step 10 - AI Specialised Customer Service Chatbot Project Combine prompt engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 - Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 - Machine Learning Project Put your machine learning knowledge into practice with a hands-on project. Step 13 - AI & Data Ethics Study the ethical considerations in AI, including issues of bias, fairness, and data privacy. Step 14 - Oral Exam Complete a virtual oral exam to assess your understanding and ability to apply your learning. Step 15 - AWS Certified Cloud Practitioner Finish with the AWS Certified Cloud Practitioner course and exam to gain essential cloud computing knowledge. They Get You Hired They 're not new to this. The company has 15+ years of experience and has placed over 5,000 people into new roles. Their job programmes include certified tutors, UK-accredited qualifications, and one-on-one support from a recruitment adviser focused on placing you. They don't believe in empty promises. Complete their programme, follow the process, and if you don't land a job, you get your money back. "Five months from complete beginner to AI engineer. Best decision I ever made." - Jamie W., now working as a Junior AI Engineer in London Ready to Start? If you're motivated, curious, and excited about technology, they'll help you turn that into a career you can be proud of. Apply now, and one of thier expert Career Advisors will be in touch within 4 working hours to guide you through your next steps.

Senior AI Engineer £700 p/d (Outside IR35) - Hybrid, Central London A leading Asset Management firm in Central London is seeking a highly technical, delivery‑focused AI Engineer to accelerate the build‑out of AI automation across critical internal operations. We're looking for someone who can combine deep engineering ability, strong systems thinking, and the ability to listen, understand, and translate stakeholder needs into reliable AI‑powered workflows. You'll be the first specialist within a new AI & Data function, owning solutions end‑to‑end and setting engineering standards from day one. What You'll do: Map human‑heavy processes and identify automation opportunities. Build robust, well‑structured AI systems using ChatGPT Enterprise. Implement retrieval workflows, decision trees, guardrails, and scalable prompt patterns. Develop high‑value internal copilots and productivity tools. Integrate AI workflows with HR, CRM, and other internal platforms. Work closely with stakeholders - listening, probing, and shaping solutions around real needs. Essential Experience Experience automating human-centric processes (approvals, performance workflows, document generation, analytics, etc.). Proven experience building AI agents and multi‑step automation flows. Strong hands‑on engineering skills (clean, explainable, well‑structured code). Expertise using ChatGPT Enterprise for workflow automation. Skilled in designing prompts, guardrails, and evaluation logic for reliable outputs. Experience building retrieval pipelines (RAG), vector search, or context‑aware systems. Comfortable integrating AI systems with APIs and internal platforms. How to Apply If you're an AI Engineer who wants to make a tangible impact by building real automation inside a major financial organisation, I'd love to hear from you. Send your CV over to (url removed) ASAP Modis International Ltd acts as an employment agency for permanent recruitment and an employment business for the supply of temporary workers in the UK. Modis Europe Ltd provide a variety of international solutions that connect clients to the best talent in the world. For all positions based in Switzerland, Modis Europe Ltd works with its licensed Swiss partner Accurity GmbH to ensure that candidate applications are handled in accordance with Swiss law. Both Modis International Ltd and Modis Europe Ltd are Equal Opportunities Employers. By applying for this role your details will be submitted to Modis International Ltd and/ or Modis Europe Ltd. Our Candidate Privacy Information Statement which explains how we will use your information is available on the Modis website

Role- Data Scientist Location: London, UK Type of job : Contract Work mode : Hybrid- 2 days onsite in a week Responsibilities: \* Explore, clean, and analyse large, complex datasets to uncover patterns, trends, and opportunities that drive actionable insights. \* Develop, train, and validate machine learning, statistical, and predictive models that solve real business problems and deliver measurable impact. \* Design and run experiments (A/B tests, hypothesis tests, simulations) to evaluate ideas, quantify outcomes, and guide decision‑making. \* Collaborate with data engineers, analysts, product managers, and domain experts to translate business requirements into well‑defined modelling tasks. \* Build end‑to‑end ML pipelines—from feature engineering and preprocessing to deployment‑ready model outputs. \* Apply advanced techniques such as NLP, time‑series forecasting, anomaly detection, optimisation, or LLM/GenAI methods where relevant. \* Implement model evaluation frameworks using offline metrics, cross‑validation, online experiments, and human‑in‑the‑loop feedback loops. \* Communicate insights clearly through dashboards, visualisations, written summaries, and presentations tailored to technical and non‑technical stakeholders. \* Ensure models are interpretable and explainable where required, providing transparency into key drivers and assumptions. \* Work with engineering teams to deploy models into production, monitor performance, and retrain or recalibrate as data and conditions change. Essential skills: Hands-on experience with GenAI, Gemini or Open source LLMs and develop GenAI applications for Code Translation, Text Extraction, Summarisation and SDLC Optimization etc. \* Hands-on Experience with AI Agents, Chat bots, RAG (Retrieval-Augmented Generation), and vector databases. ( PG vector / croma DB ) \* Hands-on Experience with GenAI Performance Evaluation tools like Pegasus, Ragas, DeepEval \* Create Conversational Interface with React JS or other Frontend components, Develop and deploy AI agents using LangGraph and ADK, A2A, MCP \* Strong programming skills in Python (experience with LangChain/LangGraph / LangSmith frameworks) and TypeScript ( preferable ) \* Solid understanding of LLMs, prompt engineering, and graph-based workflows. \* Knowledge and implementation of Input and Output guardrails in addressing Hallucination, PII filtering, HAP and Bias etc. \* Implemented security best practices, Experience to address spikes and Denial of wallet attacks, DDoS attack and other Spike arrest strategies \* Knowledge of API Gateways and ISTIO , ability to Diagnose and intercept failures in End to End communication \* Hands-on Experience with API Development and Microservices architecture Desirable experience: \* Strong experience applying machine learning, statistical modelling, and predictive analytics to real‑world business problems. \* Collaborate with cross-functional teams to ability to resolve end to end connectivity and Data Integrations \* Experience working with large, complex datasets, including data cleaning, feature engineering, and exploratory data analysis. \* Familiarity with LLMs, NLP techniques, and GenAI frameworks, including embeddings, prompt engineering, or fine‑tuning. \* Experience building end‑to‑end ML pipelines, including model validation, optimisation, deployment, and monitoring. \* Understanding of MLOps practices, including model versioning, model registries, CI/CD for ML, and automated training/inference workflows. \* Ability to translate business problems into analytical tasks and communicate insights in a clear, concise manner to technical and non‑technical audiences. \* Knowledge of data governance, including data quality, lineage, ethics, privacy considerations, and responsible AI principles. \* Comfort working with cloud platforms (GCP preferred) for model training, deployment, and scalable compute. \* A growth‑oriented mindset with enthusiasm for exploring new algorithms, tools, and emerging AI/ML techniques

Senior Full-stack Python Typescript AI Engineer- Outside IR35 ROLE This position is for a Senior Backend Developer working in python and typescript to support the development on a SaaS product with a focus on Ai. This role involves designing, building, and optimising scalable backend services and APIs to support a single-tenant, multi‑instance SaaS platform, while contributing to the architecture and implementation of AI‑driven components such as Retrieval‑Augmented Generation (RAG) pipelines, vector databases, semantic search, and structured or knowledge‑graph‑based data modelling approaches. You will support the design of robust data models and pipelines capable of handling both structured and unstructured data with strong traceability and auditability, and help transition prototypes into production‑ready systems with a focus on security, access control, performance, reliability, observability, and monitoring. The role also includes building and managing integrations with external data sources and APIs, collaborating closely with a small, cross‑functional team of developers and stakeholders to refine requirements and deliver iteratively, and contributing to best practices across development standards, testing, and deployment processes. REQUIREMENTS: Strong experience as a backend or full-stack developer with a backend focus Strong proficiency in key scripts, such as Python and TypeScript Proven experience building production-grade SaaS applications Development experience with AI/LLM system architecture, including: RAG pipelines Vector databases (e.g. Pinecone, Weaviate, FAISS, etc.) experience with relational databases (e.g. PostgreSQL) and data modelling Familiarity with API design and integration (REST or GraphQL) experience working with cloud environments (e.g. AWS, Azure, GCP) Job Title: Senior Full-stack Python Typescript AI Engineer Location: London, UK Job Type: Contract Trading as TEKsystems. Allegis Group Limited, Maxis 2, Western Road, Bracknell, RG12 1RT, United Kingdom. No. (phone number removed). Allegis Group Limited operates as an Employment Business and Employment Agency as set out in the Conduct of Employment Agencies and Employment Businesses Regulations 2003. TEKsystems is a company within the Allegis Group network of companies (collectively referred to as "Allegis Group"). Aerotek, Aston Carter, EASi, Talentis Solutions, TEKsystems, Stamford Consultants and The Stamford Group are Allegis Group brands. If you apply, your personal data will be processed as described in the Allegis Group Online Privacy Notice available at (url removed)> To access our Online Privacy Notice, which explains what information we may collect, use, share, and store about you, and describes your rights and choices about this, please go to (url removed)> We are part of a global network of companies and as a result, the personal data you provide will be shared within Allegis Group and transferred and processed outside the UK, Switzerland and European Economic Area subject to the protections described in the Allegis Group Online Privacy Notice. We store personal data in the UK, EEA, Switzerland and the USA. If you would like to exercise your privacy rights, please visit the "Contacting Us" section of our Online Privacy Notice at (url removed)/en-gb/privacy-notices for details on how to contact us. To protect your privacy and security, we may take steps to verify your identity, such as a password and user ID if there is an account associated with your request, or identifying information such as your address or date of birth, before proceeding with your request. If you are resident in the UK, EEA or Switzerland, we will process any access request you make in accordance with our commitments under the UK Data Protection Act, EU-U.S. Privacy Shield or the Swiss-U.S. Privacy Shield

Job title: Transformation Principal Pricing Analyst

Location: Peterborough, Manchester, London, Stoke-on-Trent (flexible hybrid working)

We support remote working with occasional travel to our offices.

Are you ready to use your technical expertise to help transform pricing capabilities? At Markerstudy, we’re on a mission to redefine how we deliver value to our customers and the business. This is your opportunity to join our Pricing Transformation team and play a key role in shaping the future of pricing across one of the UK’s leading insurance providers.

Why this role matters

As Transformation Principal Pricing Analyst, you’ll combine advanced technical skills with thought leadership to deliver innovative pricing solutions that maximise value for both customers and the business. You’ll provide technical leadership on modelling and optimisation, champion best practices, and coach team members to embed cutting-edge methodologies across the department. Ultimately, you’ll play a pivotal role in driving the evolution of our pricing capability and ensuring we stay ahead in a fast moving market.

What you’ll do:

• Lead the development and maintenance of predictive models (GLMs) and price optimisation techniques, including machine learning algorithms (GBM), Lifetime Value models (LTV), and fair pricing principles.
• Provide technical leadership on WTW Radar and Emblem, driving effective and efficient solutions.
• Research, develop, and champion best practice methods; upskill the team through coaching and code reviews.
• Query and engineer large datasets (e.g., Python/R/SQL/PySpark) on modern platforms (e.g., Azure Databricks).
• Communicate pricing proposals and insights clearly and persuasively to stakeholders at all levels.
• Collaborate with Modelling, Optimisation, and Street Pricing teams to ensure solutions meet business objectives and are production ready.
• Coach and mentor team members, fostering a culture of innovation and continuous improvement.

What we’re looking for:

• Previous experience in general insurance pricing.
• Strong technical expertise in predictive modelling techniques (e.g. GLMs and machine learning models).
• Proficiency in programming languages such as R, Python, PySpark, SAS, or SQL.
• Good knowledge of Azure Databricks and modern data technologies.
• Experience with WTW Radar software and optimisation tools.
• A quantitative degree in Mathematics, Statistics, Engineering, Physics, Computer Science, or Actuarial Science.
• Excellent communication skills to convey complex technical concepts to technical and non-technical audiences.
• A passion for innovation, continuous improvement and challenging the norm.

What we offer

• A collaborative, fast-paced environment where innovation thrives.
• Private medical insurance, life assurance (4x salary), and yearly bonus scheme.
• 25 days annual leave increasing with length of service, plus bank holidays (with options to buy more).
• Modern, vibrant offices and flexible hybrid working.
• Clear opportunities for career progression and professional development.

About Markerstudy

Markerstudy Group is one of the UK’s leading insurance providers, known for its innovative approach and rapid growth. With over 6,000 colleagues and 8 million customers, we deliver a wide range of motor, home, pet, and specialist insurance products through well-known brands like Swinton, Carole Nash, and Marmalade.

We’re passionate about using data, technology, and creativity to make insurance smarter and more accessible. Joining our Pricing team means you’ll work across multiple areas of the business, gaining exposure to a wide variety of challenges and opportunities. You’ll be central to shaping customer pricing strategies, driving value, and influencing decisions at the heart of a dynamic, forward-thinking organisation.

As a business committed to sustainability and investing in its people, we’re proud to hold Investors in People Gold accreditation. We offer clear opportunities for career progression, professional development, and the chance to make a real impact in a growing organisation where your work truly matters.

Ready to make your mark? Apply now and help lead the future of pricing transformation at Markerstudy.

We are looking for aMachine Learning Ops Engineerto help operationalise machine learning across Affinity Water on a 24 month FTC. Youll work with data scientists, engineers, architects, and stakeholders to deploy, monitor, and maintain ML models in robust, scalable, and secure production environments, turning advanced analytics into sustained business value.

What Youll Do

• Build, maintain, and optimise automated ML deployment pipelines with CI/CD, containerisation, and orchestration.
• Monitor model performance, data drift, and system health to ensure reliability and availability.
• Support ML platforms and infrastructure on-premise or in the cloud (AWS, SageMaker), ensuring scalability and security.
• Collaborate with data scientists to productionise models and embed ML Ops best practices across the organisation.
• Ensure governance, compliance, documentation, and reproducibility of ML pipelines and models.
• Provide 2nd/3rd line support, manage release cycles, and resolve incidents efficiently.
• Continuously improve ML Ops processes, tooling, and automation for efficiency and reliability.

What Were Looking For

Essential:

• 5+ years experience in MLOps, DevOps, or related roles.
• Strong knowledge of ML lifecycle management, deployment, monitoring, and model maintenance.
• Hands-on experience with Python (and ML frameworks), containerisation (Docker/Kubernetes), CI/CD pipelines, and cloud ML services (AWS SageMaker preferred).
• Experience with infrastructure-as-code, production-grade Linux environments, and API services (Flask/Gunicorn).
• Proficiency in building automated, reliable ML pipelines with structured and unstructured data.
• Excellent problem-solving, analytical, and communication skills; self-motivated and organised.
• Ability to embed best practices for governance, reproducibility, and operational excellence.

Desirable:

• Experience with feature stores, model registries, real-time serving, and model retraining automation.
• Integration of ML systems into business applications or APIs.
• Exposure to Water Industry data, systems, and processes.

Benefits:

• Salary: From £60,000 dependant on skills and experience
• Able to work from the Hatfield office at least 2 days per week, with flexibility to spend additional days on-site as required by the programme
• Learning and development opportunities, including mentoring and a range of formal courses and open learning resources.
• Entry into the company annual bonus scheme
• Annual leave from26-30rising with length of service, and the option to purchase up to 5 extra days.
• A Celebration Day in addition to public holidays that people can use to celebrate a religious festival or other occasion that is important to them.
• A generous ‘double match pension scheme’ that doubles the contributions you make (company contribution capped at 12%)
• We offer a range of family benefits including enhanced Maternity, Adoption, Paternity, Shared Parental Leave, Fertility Support Leave and up to 5 full or 10 half days of paid Carers Leave.
• Menopause policy and Reasonable Adjustment policy to help everyone perform at their best.
• Access to our Wellbeing Centre with support for looking after your physical and mental health.
• Discounts at a Range of Retail Outlets and on Dental and Medical Insurance through our Tap4Perks scheme.
• Up to 4 Affinity days a year to volunteer in the community.
• Life Assurance.

Disability Confident

As a Disability Confident employer, were committed to offering interviews to disabled candidates who meet the essential criteria and opt in on the application form. Ask the Talent Acquisition lead for the full job description to see all the criteria. If we have a very high volume of applicants and were not able to offer interviews to all, well take a fair and proportionate number of disabled candidates through.

Affinity Water recognises the benefits of greater diversity in our workforce to better reflect the communities we serve. We are committed to building a more inclusive culture where every member of our workforce can thrive.

Company Overview

We are working with an innovative organisation that recognises the increasing complexity of project delivery. Since 2013, our client has been helping companies of all sizes improve the way projects are delivered.

Their mission is to become the number one provider of innovative project solutions, driven by a community of experienced, caring, and passionate professionals who are committed to improving project delivery.

Why Join Our Client?

Our client is currently in an exciting phase of growth, making this an excellent time to join their journey.

They are building something special-scaling the business while maintaining a strong people-first approach. Investment in their teams is a key priority, creating an environment where development is encouraged and individuals are supported to grow with the organisation.

Their culture sets them apart from other consulting practices, and they are looking to build a team that is equally ambitious.

Position Overview

Our client is seeking a Senior Data Engineer who thrives on building scalable, cloud-first data systems.

In this role, you will design and manage data pipelines that support analytics, AI, and automation across complex infrastructure programmes. Your work will play a key part in enabling data-driven transformation across critical UK industries.

Core Responsibilities

• Design, build, and optimise data pipelines using Azure Data Factory, Synapse, and Databricks
• Develop and maintain ETL/ELT workflows to ensure high data quality and reliability
• Collaborate with analysts and AI engineers to deliver robust and reusable data products
• Manage data lakes and warehouses using formats such as Delta Lake and Parquet
• Implement best practices for data governance, performance, and security
• Continuously evaluate and adopt new technologies to evolve the organisation’s data platform
• Provide technical guidance to junior engineers and contribute to team capability building

Technical Stack

Core:

• Azure Data Factory
• Azure Synapse Analytics
• Azure Data Lake Storage Gen2
• SQL Server
• Databricks

Enhancements:

• Python (PySpark, Pandas)
• CI/CD (Azure DevOps)
• Infrastructure as Code (Terraform, Bicep)
• REST APIs
• GitHub
• Actions

Desirable:

• Microsoft Fabric
• Delta Live Tables
• Power BI dataset automation
• DataOps practices

What You’ll Bring

• Professional experience in data engineering or cloud data development
• Strong understanding of data architecture, APIs, and modern data pipeline design
• Hands-on experience within Microsoft’s Azure ecosystem, with an interest in emerging technologies such as Fabric, AI-enhanced ETL, and real-time data streaming
• Proven ability to lead technical workstreams and mentor junior team members
• A strong alignment with the organisation’s IDEAL values: Integrity, Drive, Empathy, Adaptability, and Loyalty

Ready to Apply?

This is a fantastic opportunity to join a forward-thinking organisation at a key stage of growth, working on impactful projects across critical industries.

If you’re looking to take the next step in your career within a collaborative and innovative environment, we’d love to hear from you.