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Actuary (Internal Model) - Canada Life Limited

Canada Life Limited

Location: London

Canada Life UK looks after the retirement, investment and protection needs of individuals, families and companies. We help to build better futures for our customers, our intermediaries and our employees by operating as a modern, agile and welcoming organisation.

Part of our parent company Great-West Lifeco, Canada Life UK has operated in the United Kingdom since 1903. We have hundreds of respected and supported employees committed to doing the right thing for our customers and colleagues.

Canada Life UK is transforming to create a more customer-focused business by providing our customers with expertise on financial and tax planning, offering home finance and annuities propositions, and providing collective fund solutions to third party customers.
Job Purpose
As a model implementation actuary within the internal model team at Canada Life, you will be responsible for designing, developing, supporting, testing and documenting Canada Life’s internal models. Ensuring that our internal models meet the needs of users and adhere to Canada Life’s model governance and regulatory requirements.

Key Accountabilities
• Design, develop, support, test and document internal models for credit, interest rate, inflation and equity release mortgages.
• Support the internal model operations team, investigating internal model queries, and proposing solutions.
• Work closely with the internal model design team, to understand new feature developments, and contribute to how these can be implemented within the internal model code
• Act as a conduit between the internal model team and IT to ensure our models are supported by IT and our processes are aligned with other development teams.
• Ensure internal models follow best practice standards
• Manage, coach, develop and motivate junior member of the team to support their development.
• Contribute knowledge sharing to the internal model implementing team

Desired Knowledge / Experience / Skills
Technical Expertise
• Strong capital modelling experience in market, credit and/or equity release mortgage risk space within life insurance industry.
• Experience with using python. Ideally knowledge of good software design principles and unit testing
• Experience with DevOps or GitHub for managing software developments.
• Knowledge of SII and IFRS17
• Use of generative AI

Communication
• Strong communication skills, demonstrating a clear and articulate standard of written and verbal communication in a complex environment, tailored for all levels of management.
• Strong ability to adapt messages to the audience, without prompting or significant coaching, in a format that is easily understood by non-technical colleagues

Relationship Building
• The ability to develop and maintain strong relationships across the actuarial function, IT and the wider business, acting with integrity and role modelling the company values at all times.
• Ability to flex their style and delivery, in the moment, depending on the individual and/or audience.

Taking Initiative
• Exceptional problem solving skills and attention to detail with demonstrable ability in spotting issues, interdependencies and challenges to ensure work is produced to an accurate, commercial and informed standard.
• Self-motivated, well-organised, pragmatic and able to perform tasks independently.

Developing Self and Others
• Strong skills and experience in managing and motivating a team from a diverse range of professional backgrounds and with varying levels of experience
• Strong coaching ability in technical, and non-technical skills in order to support the development of others.
• An interested and inquisitive individual who is committed to their own ongoing professional and personal development

Qualifications
• Fellow of Institute of Actuaries (or equivalent).

Benefits of working at Canada Life
We believe in recognising and rewarding our people, so we offer a competitive salary and benefits package that’s regularly reviewed. As a Canada Life UK colleague, you’ll receive a competitive salary and comprehensive reward package including a generous pension and bonus scheme, along with, income protection, private medical insurance and life assurance. We have a fantastic number of other benefits and support services as well as regular personal and professional development.

How we work at Canada Life
Our culture is unique and incredibly important to us. We care about doing the right thing for our people, customers and community and helping others to build better futures. Our blueprint behaviours shape and influence how we work, and are central to the relationships we have with others. Every day we are encouraged to be more curious, own the outcome, face into things together and find a way forward.

We want colleagues to have rewarding careers with us so we invest in the development of our people, technology and workplaces. That’s why we offer a range of training, flexible working and opportunities to grow and develop.

Diversity and inclusion
Building an inclusive workplace with a diverse workforce where everyone can feel they belong and achieve their potential regardless of gender, ethnicity or any other characteristic is a key commitment for us. We are proud of the progress we’re making in DEI, and we continue for it to be a significant focus.

“At Canada Life we believe in the power of great people from different backgrounds, experiences and perspectives coming together to build better futures. Emerging talent is crucial to our growth and creating an environment that continues to inspire us all.” Nick Harding, Chief People Officer, Canada Life UK

We appreciate that everyone has different work and life responsibilities. We’re happy to discuss flexible working arrangements, including part time, for any of our roles should this be a requirement for you.

Machine Learning Engineer - TradingHub

Compensation: Competitive (Financial Services)

About TradingHub

Founded in 2010, TradingHub delivers uniquely intelligent trade surveillance software to world leading financial institutions. Developed by market professionals, our solutions use sophisticated modelling techniques to detect single and cross-product market manipulation.

With a team of over 150 experts worldwide, TradingHub combines global reach with deep markets expertise to help our customers mitigate financial, regulatory, and reputational risk.

The Role

We’re looking for a Machine Learning Engineer to join our Analytics division and play an important role in enhancing our metrics offering. As our first dedicated ML hire, you’ll be utilising an array of modern LLM and NLP techniques to analyse complex financial data and unlock new capabilities for our market-leading suite of trade surveillance products.

This role will see you combine hands-on model development and software engineering, and collaborate with a high-performing team of Quant Researchers and Developers as well as other cross-functional departments.

Responsibilities:

Design, develop, and deploy machine learning models to enhance TradingHub’s market surveillance and analytics platform
Contribute to the development of advanced metrics used to analyse trader behaviour, order execution and potential market abuse scenarios
Apply machine learning and statistical techniques to large-scale financial datasets, improving accuracy and reducing false positives
Leverage LLM and NLP models to extract insights from unstructured data and integrate them into existing analytics workflows
Collaborate closely with quantitative developers, data engineers, and product teams to productionise models into scalable, high-performance systems

Requirements

Confident programming skills in Python, with experience using modern ML frameworks (e.g. PyTorch, TensorFlow, scikit-learn)
Good understanding of core machine learning concepts such as linear regression, reinforcement learning and deep learning
Industry experience using Large Language Models (LLMs) to deliver commercial value
Experience building data pipelines and performing feature engineering on real-world datasets
Strong problem-solving skills and attention to detail
Good understanding of SQL and working with complex datasets
Keen interest in financial markets e.g. pricing, trading, fixed income

Benefits

Life at TradingHub is a rewarding journey within a fast-growing company that thrives on innovation and collaboration. By combining the best of technology and global markets, we’re able to solve complex problems together and deliver meaningful results to our customers. Everybody has value to bring, and we welcome individuality as a key driving force behind our collective success.

Rooted in everything that we do are our core values: Accountability, Ambition, Partnership and Trust. These values provide the foundation for a sustainable workplace culture that empowers you to grow, contribute, and become your best self.

Employee Benefits:

Annual discretionary performance bonus (permanent employees only)
Hybrid working policy
Office lunches twice a week
Private medical insurance + dental cover
Extended parental leave (up to 6 months of fully paid maternity leave)
25 days annual leave + bank holidays
Enhanced company pension plan
5 days study leave towards professional qualifications
Salary sacrifice schemes
Death in service coverage

Don’t tick every single requirement? Research shows that candidates from under-represented groups are less likely to apply unless they meet all the criteria. We are dedicated to building a diverse, equitable and inclusive workplace, so if this role excites you, please don’t let our specification hold you back. Get in touch!

TradingHub is an equal opportunities employer. We do not discriminate based on race, religion, ethnic or national origins, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, socio-economic background, responsibilities for dependants, physical or mental disability or other applicable legally protected characteristics. TradingHub selects candidates for interview based solely on their skills, experience and qualifications.

We are committed to making our recruitment process accessible to all and we encourage candidates to inform us of any required adjustments. A full copy of our diversity, equity and inclusion policy will be made available to you upon request.

Company Description

Experian is a global data and technology company, powering opportunities for people and businesses around the world. We help to redefine lending practices, uncover and prevent fraud, simplify healthcare, create marketing solutions, and gain deeper insights into the automotive market, all using our unique combination of data, analytics and software. We also assist millions of people to realize their financial goals and help them save time and money.

We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more industry segments.

We invest in people and new advanced technologies to unlock the power of data. As a FTSE 100 Index company listed on the London Stock Exchange (EXPN), we have a team of 22,500 people across 32 countries. Our corporate headquarters are in Dublin, Ireland. Learn more at experianplc.com.

Job Description

We are looking for a Product Manager to join our UKI Marketing Services team, reporting into the product director. You will help scale AI-enabled, data-driven products across our portfolio. This is an exciting opportunity to work at the intersection of AI and data, where you will help launch products and ensure they deliver value for clients. You’ll focus on translating strategy into execution, embedding AI capabilities into products, and driving adoption, performance, and continuous improvement.

You’ll be part of a collaborative Product Pod, working closely with engineering, data, design, and go-to-market teams to create high-quality, scalable solutions.

What you’ll do

Deliver and scale AI-enabled products. Support the delivery and continuous improvement of data and AI-powered products, ensuring they meet client needs and drive measurable outcomes.
Translate strategy into actionable roadmaps. Own and evolve product roadmaps in consideration of broader AI and data strategy, ensuring clear priorities and outcomes within your product scope.
Embed AI capabilities into products. Work with data and AI teams to integrate reusable AI capabilities into products, accelerating innovation and consistency across the portfolio.
Improve product performance and optimisation. Monitor product performance, identify opportunities for improvement, and iterate to increase adoption, client value, and commercial impact.
Collaborate across cross-functional teams. Partner closely with Product Owners, engineers, data scientists, and GTM teams to ensure delivery.
Understand users and market context. Build understanding of client needs, user journeys, and market trends to inform product enhancements and prioritisation.
Support go-to-market execution Work with commercial and marketing teams to position products clearly, ensure they understand them well, launch and promote their adoption.
Maintain product quality and compliance Ensure you follow product lifecycle processes, documentation, and governance requirements consistently.

Qualifications

Experience in product management within a data-driven environment
Experience delivering products or features end-to-end, from concept through to launch and optimisation
Experience working in cross-functional teams (e.g. engineering, data, design, and commercial)
You will have product management experience in marketing services or data products
Degree or equivalent practical experience in a relevant field (e.g. business, technology, data, and marketing)

Additional Information

Benefits package includes:

Hybrid working - 40% office based
Great compensation package and discretionary bonus plan
Core benefits include pension, bupa healthcare, sharesave scheme and more!
25 days annual leave with 8 bank holidays and 3 volunteering days. You can also purchase additional annual leave.

Internal Grade EB8/D

Our uniqueness is that we celebrate yours. Experian’s culture and people are important differentiators. We take our people agenda very seriously and focus on what matters; DEI, work/life balance, development, authenticity, collaboration, wellness, reward & recognition, volunteering… the list goes on. Experian’s people first approach is award-winning; World’s Best Workplaces 2024 (Fortune Top 25), Great Place To Work in 24 countries, and Glassdoor Best Places to Work 2024 to name a few. Check out Experian Life on social or our Careers Site to understand why.

Experian is proud to be an Equal Opportunity and Affirmative Action employer. Innovation is an important part of Experian’s DNA and practices, and our diverse workforce drives our success. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, colour, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.

Experian Careers - Creating a better tomorrow together

Find out what its like to work for Experian by clicking here

#LI-ST1 #LI-Hybrid

Experian Careers - Creating a better tomorrow together

Find out what its like to work for Experian by clicking here

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Salary to £45k + Company Options Scheme Hybrid working between your home, their offices (London Vauxhall) & client sites. NB: Please only apply if you are a UK National and able to achieve SC (ideally DV) clearance i.e. you have at least 5 years residency in the UK with no more than a 3 month break outside the UK. This company is a Workflow & AI Orchestration Specialist. They're on a mission to modernise how public sector organisations manage casework, derive insight from data and deliver citizen services. Theyre growing fast and looking for bright, dynamic people to help build their business. Role Theyre looking for aJava Engineer to join their implementation team. Youll work across Camunda BPMN/DMN process automation, API integration, and microservice orchestration helping their public-sector clients build secure, scalable, and resilient digital services. Youll collaborate with solution architects, business analysts, and designers to translate workflows into elegant, maintainable code. Youll play a key part in defining technical standards, optimising runtime performance, and mentoring less- experienced engineers in workflow-centric delivery. This is an ideal role for someone who enjoys solving complex process problems through clean code, automation, and modern engineering practices. The role involves visiting client sites; the company will cover travel expenses. Frequency is uncertain but candidates should be comfortable with that being 2-3 days per week. Client sites could be anywhere but will most likely be in & around London. Responsibilities Design, develop, and deploy Camunda-based process and decision automation solutions Implement and integrate Java-based microservices, APIs, and connectors within orchestration flows Translate BPMN and DMN models into executable workflows and reusable components Collaborate closely with analysts and service designers to refine and iterate business processes Develop and maintain automated test suites, CI/CD pipelines, and containerised deployments Optimise Camunda engine performance and monitor workflow metrics for production environments Participate in code reviews, peer testing, and technical design discussions Contribute to their internal best-practice frameworks and automation accelerators Essential Eligible (have resided in the UK for the past 5 years) and prepared to go through UK SC Security Clearance Experience in Java software engineering and object-oriented design Spring (Boot) experience Experience with REST APIs, and microservice architectures Knowledge of Docker and Kubernetes for containerisation and orchestration Proficiency in Git, CI/CD pipelines, and automated testing frameworks Understanding of event-driven design and message brokers (e.g. Kafka, RabbitMQ) Good knowledge of security, authentication, and integration patterns for enterprise systems Experience working in agile teams within digital transformation or automation programmes A willingness to learn BPMN and Camunda tooling Some exposure to process automation or microservice orchestration Desirable Experience with Camunda 8 (Zeebe) clusters and Operate/Tasklist components Experience implementing solutions using Camunda 7 or 8 (BPMN/DMN) Familiarity with Camunda connectors, external task workers, and scripting extensions Exposure to cloud platforms (AWS, Azure, GCP) and infrastructure-as-code (Terraform, Helm) Experience integrating process automation with case-management or service-orchestration platforms Understanding of agentic AI capabilities and how they can complement workflow automation Experience mentoring developers or contributing to open-source Camunda extensions Already holding UK security clearance (SC, DV, eDV) Other Stuff NB: Please only apply if you are a UK National and able to achieve SC or DV clearance. i.e. you have at least 5 years residency in the UK with no more than a 3 month break outside the UK. NB: for non-UK Citizens; we cannot accept applications from anyone requiring sponsorship (now or in the future) for UK permanent employment status. If you are utilising a work visa this must allow you to work in the UK unrestricted for at least the next 5 years. Profile 29 recruitment keywords: Java software engineer object-oriented design OOD Camunda BPMN DMN Spring Boot REST API microservice architecture Docker Kubernetes containerisation orchestration Git CI/CD pipelines automated testing frameworks Kafka RabbitMQ Security authentication integration patterns enterprise systems agile digital transformation automation Java developer Camunda developer Zeebe Cloud AWS Azure GCP Terraform Helm process automation agentic AI artificial intelligence security clearance SC DV eDV London home based hybrid junior jnr

Birmingham | Hybrid £55,000 – £65,000 + excellent benefits We are partnering with an established, customer-focused business based in Birmingham that continues to invest significantly in its data and technology capabilities. They are seeking to appoint a Senior Data Engineer to play a pivotal role in developing their Azure data estate and to drive the next phase of their platform modernisation journey. This is an excellent opportunity for a hands-on engineer who thrives on ownership, influencing technical direction, and collaborating closely with the wider business to deliver impactful data solutions. The role offers a genuine blend of technical delivery, platform enhancement, and leadership exposure What's the job? You will be responsible for leading the design, development and optimisation of scalable data solutions within a modern Microsoft Azure environment. A key focus of the role will be enhancing data integration, modelling, and accessibility to support reporting and operational decision-making, while facilitating the ongoing migration from legacy systems to Azure. You will collaborate closely with internal Business Intelligence and technology teams, helping to establish best practises across data engineering and platform performance. Key Responsibilities Lead the design and optimisation of data pipelines and ETL/ELT workflows Develop scalable solutions across Azure Synapse, Data Factory, and Data Lake Support the ongoing evolution of the wider Azure data platform Enhance data models and reporting layers that underpin downstream BI solutions Collaborate with stakeholders across operations, finance, and technology teams Define and promote best practises around data quality, security, and governance Support cloud migration and platform modernisation initiatives Drive continuous improvement in performance, automation, and reliability Provide technical leadership and guidance across engineering projects Person Specification We welcome applications from strong engineers with solid experience across the Microsoft data stack, particularly: Azure Synapse Azure Data Factory Azure Data Lake SQL ETL/ELT pipeline development Power BI data modelling and reporting integration Experience with SSIS, SSRS, or legacy SQL environments (desirable) Most importantly, we seek someone who combines strong technical expertise with a commercial mindset and a collaborative approach. You are not expected to meet every requirement. Strong Azure data engineering experience remains the key priority. Why This Opportunity Is Worth Exploring Greater ownership and influence A modern Azure cloud environment A visible, impactful role within the business Long-term career progression opportunities A balanced blend of hands-on technical work and leadership exposure

C++ Developer - London Stock Exchange Group

London Stock Exchange Group

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Real-Time Software Engineer (C++) - News Engineering @ LSEG

Help us shape the future of real-time news delivery and join a team powering the heartbeat of global information! LSEG’s News Engineering group is looking for Software Engineer to help evolve our real-time news collection and distribution platform. If you’re motivated by high-performance systems, real-world impact, and incorporating modern engineering practices in a dynamic and forward-thinking environment - this is your opportunity.

This role is ideal for mid-level engineers who thrive as individual contributors and want to grow their expertise in real-time systems, C++, and cloud-native development.

As a software engineer in the News team at LSEG, you will write clean, efficient C++ and Python code for both on-prem and cloud-hosted environments. Work with structured data formats like XML, JSON, HTML, and XSLT - and learn how they power News industry standards. Collaborate in a scrum team crafting solutions and delivering new features. Be responsible for your code by writing automated tests, participating in code reviews, and supporting production systems. Help automate deployment, upgrades, and maintenance using modern DevOps tools. Occasionally provide on-call support for critical systems (we keep it reasonable).

What We’re Looking For

• Solid experience with C/C++ on Linux and real-time systems.

• Experience with cloud infrastructure and container orchestration.

• Practical experience in using IP-based protocols (TCP/IP, UDP, HTTPS, etc)

• Familiarity with unit testing, especially using Google Test.

• Understanding of network protocols and distributed systems.

• Strong problem-solving skills

• Ability to work independently and communicate clearly.

Bonus Points

• Hands-on experience with Python, Google Test framework, GitLab CI/CD, Kubernetes, or Terraform

• Knowledge of NewsMLG2 or similar standards and experience implementing a standard format at speed

Why Join Us?

• Impact: Your work helps deliver critical news to millions in real time.

• Growth: Learn from expert engineers and expand your skills across cloud, data, and resilient systems.

• Culture: We value curiosity, ownership, and teamwork. You’ll work in a globally distributed team that supports each other.

• Flexibility: Hybrid work options and a balanced work-life environment

Career Stage:
Senior Associate

London Stock Exchange Group (LSEG) Information:

Join us and be part of a team that values innovation, quality, and continuous improvement. If you’re ready to take your career to the next level and make a significant impact, we’d love to hear from you.

LSEG is a leading global financial markets infrastructure and data provider. Our purpose is driving financial stability, empowering economies and enabling customers to create sustainable growth.

Our purpose is the foundation on which our culture is built. Our values of Integrity, Partnership, Excellence and Change underpin our purpose and set the standard for everything we do, every day. They go to the heart of who we are and guide our decision making and everyday actions.

Working with us means that you will be part of a dynamic organisation of 25,000 people across 65 countries. However, we will value your individuality and enable you to bring your true self to work so you can help enrich our diverse workforce.

We are proud to be an equal opportunities employer. This means that we do not discriminate on the basis of anyone’s race, religion, colour, national origin, gender, sexual orientation, gender identity, gender expression, age, marital status, veteran status, pregnancy or disability, or any other basis protected under applicable law. Conforming with applicable law, we can reasonably accommodate applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs.

You will be part of a collaborative and creative culture where we encourage new ideas. We are committed to sustainability across our global business and we are proud to partner with our customers to help them meet their sustainability objectives. Our charity, the LSEG Foundation provides charitable grants to community groups that help people access economic opportunities and build a secure future with financial independence. Colleagues can get involved through fundraising and volunteering.

LSEG offers a range of tailored benefits and support, including healthcare, retirement planning, paid volunteering days and wellbeing initiatives.

Please take a moment to read this privacy notice carefully, as it describes what personal information London Stock Exchange Group (LSEG) (we) may hold about you, what it’s used for, and how it’s obtained, your rights and how to contact us as a data subject .

If you are submitting as a Recruitment Agency Partner, it is essential and your responsibility to ensure that candidates applying to LSEG are aware of this privacy notice.

Quant Analyst ( MFT ) - London

About the Firm We are a global, technology-driven trading firm focused on digital asset markets. The business operates across major electronic trading venues, providing liquidity and execution solutions to a broad range of institutional counterparties. Alongside its core trading activities, the firm works with emerging digital asset projects and supports financial institutions expanding into the space. It also selectively invests in early-stage opportunities within the broader digital asset ecosystem. The firm combines the technical sophistication of established quantitative trading environments with the agility of a fast-scaling technology business. With a long-term perspective on digital assets, it is focused on building robust, scalable, and efficient trading infrastructure. The Role We are looking for a Quantitative Researcher with experience developing mid-frequency (MFT) or short-term systematic strategies across traditional financial markets (e.g. equities, futures, FX) or digital asset markets. You will utilise a sophisticated research and execution platform to develop, test, and deploy trading strategies in digital asset markets. Working closely with trading and engineering teams, you will refine models, improve execution, and explore new sources of alpha across a diverse set of instruments. Responsibilities 1. Develop and implement mid-frequency trading strategies (from seconds to multi-day holding periods) 2. Design predictive models to capture inefficiencies in digital asset markets 3. Analyse high-frequency and tick-level data to identify alpha signals and microstructure patterns 4. Conduct robust backtesting, simulation, and optimisation of strategies 5. Partner with engineering teams to improve execution and system performance 6. Iterate on and scale strategies across multiple trading venues Requirements 1. Experience developing systematic trading strategies with demonstrable performance 2. Strong academic background in Mathematics, Statistics, Computer Science, Engineering, or a related field 3. Proficiency in Python (C++ or other low-level languages is a plus) 4. Solid understanding of statistical modelling, time series analysis, and market microstructure 5. Interest in applying quantitative strategies to digital asset markets 6. Strong collaborative and problem-solving mindset Preferred Experience 1. Exposure to digital asset markets or related trading strategies 2. Experience in market making or liquidity provision 3. Familiarity with exchange connectivity, APIs, and electronic trading systems 4. Experience working with alternative or non-traditional datasets Why Join 1. Opportunity to work in a high-growth area within global markets 2. Direct impact on trading performance and strategy development 3. Collaborative and meritocratic team environment 4. Fast-paced, technology-driven culture with significant ownership 5. Competitive compensation aligned with performance

Senior Quantitative Researcher – Systematic Macro & Execution Alpha

Role Overview: 1. Drive research into short-horizon, high-frequency trading signals with typical holding periods of several hours to a few days 2. Take ownership of execution and market microstructure research, helping optimize trading strategy design and implementation 3. Collaborate with a cross-functional team of researchers, technologists, and portfolio managers in a highly iterative, data-driven workflow 4. Build and oversee a small, high-caliber team of junior researchers (2–3 people), contributing to both leadership and hands-on research 5. Leverage a modern research stack that includes distributed computing environments (e.g. AWS, Slurm), large-scale data tools (e.g. kdb+, Exasol), and advanced methods in statistics and machine learning Ideal Candidate Will Have: 1. 3+ years of experience in a quantitative trading or research role at a hedge fund, proprietary trading firm, or sell-side algo desk 2. Demonstrated contributions to alpha generation or strong potential to do so in a collaborative environment 3. Strong academic credentials (First Class, Honours, MSc or PhD) in a quantitative or technical field such as Mathematics, Statistics, Physics, Computer Science, Engineering, or Finance 4. Familiarity with high-frequency or tick-level data and an ability to derive actionable insights from complex datasets 5. Proficiency in Python or C++; experience with distributed computing and low-latency research environments is advantageous 6. Strong preference for candidates with kdb+/q experience and familiarity with execution protocols such as FIX 7. Confident communicator, able to clearly explain concepts, defend ideas, and work collaboratively with non-research stakeholders

Junior Quantitative Researcher – Systematic Strategies

London | Start by September 2026 We are partnering with a leading systematic investment team in London seeking an exceptional early-career Quantitative Researcher to join a high-performing, research-driven environment. This is a rare opportunity to work directly alongside experienced portfolio managers and researchers, contributing to live trading strategies from the outset. The team operates at the intersection of data science, financial theory, and advanced engineering, with a strong emphasis on original thinking and rigorous experimentation. The Opportunity From day one, you will be immersed in the research lifecycle—helping to generate, test, and refine alpha signals across liquid global markets. The role is designed for individuals who combine strong academic foundations with a genuine curiosity for markets and data. You will: 1. Develop and evaluate predictive signals using large, complex datasets 2. Design and run robust backtests across multiple asset classes and time horizons 3. Explore new modelling approaches, including statistical and machine learning techniques 4. Work closely with senior researchers and developers to translate ideas into production 5. Contribute to improving research infrastructure and data workflows Who They’re Looking For This role targets high-potential junior talent ready to step into a front-office research environment. You should meet one of the following criteria: 1. A Master’s graduate (from a leading/red-brick university) with relevant internship experience in quant research, trading, or data science 2. A recently completed or soon-to-complete PhD (2025 or 2026) in a highly quantitative discipline In addition, you will likely have: 1. Strong grounding in mathematics, statistics, physics, computer science, or a related field 2. Proven programming ability (typically Python; C++ or similar is a plus) 3. Experience working with data—cleaning, analysing, and extracting signal 4. A methodical, research-oriented mindset with attention to detail 5. A genuine interest in financial markets and systematic trading Why This Role 1. Direct exposure to live trading strategies from an early stage 2. Highly collaborative, intellectually rigorous team culture 3. Meritocratic environment where strong ideas are quickly recognised and implemented 4. Clear progression into a long-term research career within systematic investing Additional Requirements 1. Ability to start no later than September 2026 2. Right to work in the UK (or ability to secure it quickly)

Principal Machine Learning Engineer - London Stock Exchange Group

London Stock Exchange Group

About Us:

LSEG (London Stock Exchange Group) is more than a diversified global financial markets infrastructure and data business. We are dedicated, open-access partners with a dedication to excellence in delivering the services our customers expect from us. With extensive experience, deep knowledge and worldwide presence across financial markets, we enable businesses and economies around the world to fund innovation, manage risk and create jobs. It’s how we’ve contributed to supporting the financial stability and growth of communities and economies globally for more than 300 years. Through a comprehensive suite of trusted financial market infrastructure services - and our open-access model - we provide the flexibility, stability and trust that enable our customers to pursue their ambitions with confidence and clarity.

LSEG is headquartered in the United Kingdom, with significant operations in 70 countries across EMEA, North America, Latin America and Asia Pacific. We employ 25,000 people globally, more than half located in Asia Pacific. LSEG’s ticker symbol is LSEG.

Our People:

People are at the heart of what we do and drive the success of our business. Our culture of connecting, creating opportunity and delivering excellence shape how we think, how we do things and how we help our people fulfil their potential. We embrace diversity and actively seek to attract individuals with unique backgrounds and perspectives. We break down barriers and encourage teamwork, enabling innovation and rapid development of solutions that make a difference. Our workplace generates an enriching and rewarding experience for our people and customers alike. Our vision is to build an inclusive culture in which everyone feels encouraged to fulfil their potential.

We know that real personal growth cannot be achieved by simply climbing a career ladder - which is why we encourage and enable a wealth of avenues and interesting opportunities for everyone to broaden and deepen their skills and expertise. As a global organisation spanning 70 countries and one rooted in a culture of growth, opportunity, diversity and innovation, LSEG is a place where everyone can grow, develop and fulfil your potential with meaningful careers.

Role Summary

We are seeking a Principal Machine Learning Engineer (SageMaker, MLOps, Model Governance & Explainability) to provide technical leadership across the full lifecycle of machine learning systems powering a new matching platform. This role is accountable for defining ML architecture, establishing engineering standards, driving MLOps maturity, and ensuring that our models are scalable, secure, explainable, and governed to enterprise-grade standards.

You will contribute to the strategic direction of our ML platform-spanning data pipelines, model development, deployment automation, inference runtime design, telemetry, drift detection, and cross-account productionisation. You will mentor engineers, influence product and architectural decisions, and ensure that our ML systems operate reliably at scale, underpinned by a robust governance and compliance framework.

This is a highly hands-on, highly technical, principal-level role that combines architectural vision with deep practical expertise in ML engineering and AWS-native MLOps.

Key Responsibilities

Technical Leadership & Architecture

Define the end-to-end ML architecture for the matching platform, including data pipelines, model training workflows, inference runtimes, and telemetry ecosystems.
Lead adoption of best-in-class MLOps patterns, platform tooling, and AWS SageMaker capabilities across training, processing, registry, monitoring, and deployment.
Partner with platform, security, and data engineering teams to implement scalable data lakehouse oriented feature architectures and enterprise-grade ML governance.
Champion engineering standards for model quality, documentation, observability, and platform resilience.

Feature Engineering & Data Architecture

Architect highly scalable, production-ready feature pipelines within Lakehouse environments.
Set the technical direction for fallback and resilience strategies (e.g., fallback pipelines).
Establish and enforce data-quality guardrails, validation schemas, and monitoring frameworks.
Drive adoption and standards for enterprise feature stores.

Model Development & Technical Excellence

Lead the design of ranking, scoring, and similarity models tailored to the matching platform requirements.
Define model calibration, scoring logic, confidence thresholds, and optimisation strategies.
Mentor teams on advanced ML techniques using Model frameworks such as PyTorch, TensorFlow, and XGBoost.
Review and approve technical designs for complex modeling workflows.

Explainability & Regulatory-Grade Reasoning

Establish explainability standards across the ML stack, using SHAP or equivalent frameworks.
Define patterns to generate regulator-ready reason codes, aligned with compliance requirements.
Ensure explainability artefacts are accurate, robust, and traceable across model versions.

ML Deployment & Automation (MLOps)

Architect automated training, deployment, and retraining pipelines using AWS SageMaker.
Set standards for model registry usage, automated approvals, and rollback orchestration.
Drive infrastructure-as-code and CI/CD maturity for ML systems across multiple environments.
Lead design of enterprise-wide weight-update patterns and lineage-aware deployment strategies.

Inference Runtime & Cross-Account Productionisation

Architect low-latency, high-throughput inference services that meet strict matching platform SLAs.
Lead the design of secure cross-account IAM patterns for model consumption.
Own end-to-end telemetry design, including scoring metrics, latency, error analytics, and SLOs.
Partner with platform teams to optimise cost, scale, and reliability of inference endpoints.

Monitoring, Drift Detection & Observability

Define observability standards for feature drift, concept drift, performance degradation, and data integrity.
Lead the creation of dashboards, benchmarks, and automated alerting across the ML ecosystem.
Ensure telemetry pipelines adhere to privacy, data minimisation, and compliance policies.
Drive adoption of proactive failover, shadow-mode testing, and continuous validation patterns.

Security, Compliance & ML Governance

Set and enforce ML-specific security standards including data minimisation, encryption, and PII handling.
Oversee creation of Model Cards, lineage artefacts, and compliance documentation.
Ensure ML systems meet governance standards for auditability, reproducibility, versioning, and traceability.
Collaborate with InfoSec and Risk teams to define ML governance frameworks and secure cross-environment workflows.

Testing, Validation & Performance Engineering

Lead validation strategies using golden datasets, behavioural tests, and benchmark suites.
Architect performance testing for latency-sensitive inference paths and model hot paths.
Establish standards for A/B testing, shadow deployments, canary rollouts, and controlled experiments.

Principal-Level Skills & Experience

Essential

Proven track record architecting and delivering production ML systems at scale in enterprise environments.
Deep expertise with AWS SageMaker (training, processing, pipelines, endpoints, registry) and complementary AWS services.
Expert-level Python and ML Model frameworks (e.g. PyTorch, TensorFlow, XGBoost).
Strong thought leadership in MLOps automation, CI/CD for ML, and model lifecycle management.
Advanced experience designing explainability systems, reason codes, and governance artefacts.
Expertise in low-latency inference architectures and real-time model serving.
Strong grounding in drift detection, telemetry pipelines, observability patterns, and model QA.
Experience shaping ML security practices, including cross-account IAM, data minimisation, and PII-safe design.
Ability to influence architecture, mentor senior engineers, and set long-term technical direction.

Nice to Have

Experience building or leading feature store adoption.
Background in ranking, search relevance, entity matching, or similarity modelling.
Experience designing or governing multi-account AWS ML platforms.
Knowledge of distributed training, GPU/accelerator optimisation, and scaling strategies.
Bachelors in a STEM subject, e.g. mathematics, physics, engineering, computer science, or adjacent degrees.
Masters or PhD or equivalent experience in STEM desirable but not essential

Career Stage:
Manager