Role:- Quantitative researcher to help build out a new systematic macro (futures, FX, and vol) business. The main focus will be working on mid-frequency alpha strategies. 1. Develop systematic trading models across FX, commodities, fixed income, and equity markets 2. Alpha idea generation, back testing, and implementation 3. Assist in building, maintenance, and continual improvement of production and trading environments 4. Evaluate new datasets for alpha potential 5. Improve existing strategies and portfolio optimization 6. Execution monitoring 7. Be a core contributor to growing the investment process and research infrastructure of the team Requirements:- 1. PhD in mathematics, statistics, physics or other quantitative discipline. 2. Experience in quantitative trading, ideally in FX or futures 3. Experience with alpha research, portfolio construction and optimization 4. Experience building statistical/technical, fundamental, and data driven signals 5. Experience synthesizing predictive signals for both cross-sectional and time-series models 6. Strong experience with data exploration, dimension reduction, and feature engineering 7. Proficiency in Python using the machine learning stack—numpy, pandas, scikit-learn, etc. Apply:- Please send a PDF CV to quants@ekafinance.com

What You’ll Do: 1. Conduct end-to-end research on systematic strategies across liquid asset classes (equities, futures, FX, or rates). 2. Leverage large datasets, machine learning techniques, and advanced statistical modelling to uncover persistent sources of alpha. 3. Collaborate closely with other researchers, portfolio managers, and technologists in a highly integrative research culture. 4. Iterate and improve signal construction, portfolio optimization, and risk models with access to world-class infrastructure and tooling. What We’re Looking For: 1. 4–6 years of systematic research experience at a top collaborative hedge fund (e.g., Two Sigma, AQR, PDT, etc.). 2. Deep expertise in alpha signal research, with a proven track record of contributions to production strategies. 3. Strong programming skills in Python (or similar), and comfort working with large, noisy datasets. 4. A highly analytical mindset with fluency in statistics, probability, and time-series analysis. 5. Advanced degree (Master’s or PhD) in a quantitative discipline preferred, but not required. Why This Role: 1. Join a high-conviction, low-politics team that values idea meritocracy and intellectual honesty . 2. Work alongside researchers and PMs who are genuinely collaborative — not siloed or secretive. 3. Access deep resources and institutional-grade infrastructure to bring ideas to life quickly and at scale. 4. Significant upside and career growth for researchers who drive real impact.

We are seeking a talented Quantitative Researcher to develop machine learning-based models for systematic trading in digital asset and financial markets. This is a front-office research role based in the UK, offering hands-on experience with high-frequency market data, advanced ML architectures, and collaboration with a team of quantitative researchers and engineers. Responsibilities 1. Develop ML-based alpha generation models using high-frequency order book and market microstructure data 2. Design and maintain robust data pipelines, preprocessing, and feature extraction workflows for streaming tick data 3. Research and implement advanced deep learning architectures for short-horizon forecasting and signal extraction 4. Collaborate with quantitative researchers and engineers to integrate models into live trading systems 5. Optimise inference latency and ensure model robustness under live market conditions 6. Continuously refine model performance through systematic backtesting, live evaluation, and monitoring Requirements 1. Degree in Computer Science, Machine Learning, Applied Mathematics, or a related quantitative discipline 2. Strong programming skills in Python and familiarity with standard ML libraries 3. Proven experience applying ML/DL techniques to real-world problems 4. Familiarity with time-series modelling, signal extraction, or high-frequency data 5. Experience developing ML infrastructure, including data pipelines, experiment tracking, and version control 6. Collaborative mindset and problem-solving orientation Preferred Experience 1. Exposure to finance, trading, or quantitative research (helpful but not required) 2. Publications, competition results (e.g., Kaggle, academic ML contests), or open-source contributions 3. Familiarity with C++, CUDA, or other low-latency systems Why Join 1. Work at the forefront of systematic trading and digital asset markets in the UK 2. Hands-on exposure to large-scale, high-frequency data and cutting-edge ML techniques 3. Collaborative, meritocratic team environment with direct impact on strategy and performance 4. Fast-paced, technology-driven culture offering meaningful ownership and growth 5. Competitive UK-based compensation aligned with experience and performance

Role:- Initially you will be mentored by a senior member of the team and will be responsible for implementing and optimizing existing strategies. You will work on the research, design and C++ implementation of innovative data analysis algorithms and tools and the research, back-testing, C++ implementation and deployment of new trading strategies. Requirements:- PhD from a top tier University in any of the following subjects; Computer Science, Machine Learning, Artificial Intelligence, Statistics, Operations Research, Econometrics, Signal Processing, Computer Vision. They will also consider exceptional Masters level students. An understanding of how to translate your research expertise to contribute to the development and optimisation of quantitatively driven strategies and trading. Experience of working with large data sets, or noisy data. A distinguished background in research or internships at reputable organisations. Strong software programming skills in C++ ,Perl or Python. Demonstrable interest in systematic trading. A background in time series analysis, statistics, reinforced learning algorithms, portfolio theory. They are happy to consider candidates who have completed their PhD this year as well as candidates who graduate in 2018 and are looking for a role on completion of their PhD . Interviews will consist of meetings with the senior partners as well as technical rounds with the quants and developers. The environment is excellent and turnover is incredibly low. No work visa can be provided for this role.

We're building a team of top performers who thrive on solving hard problems, value precision and creativity, and are driven by results. You'll be joining a fast-paced setup that prizes autonomy, sharp thinking, and continuous learning. Who You Are: 1. You bring a deep academic foundation in a technical or quantitative subject—think Computer Science, Engineering, Physics, Statistics, Mathematics, or a closely related area. While a Ph.D. is a strong asset, we also welcome standout candidates with Bachelor’s or Master’s degrees who have demonstrated exceptional capability. 2. You have a proven track record of pushing the boundaries in your field—whether through novel research, impactful projects, or real-world applications. 3. You’re fluent in at least one major programming language used in data science or systems development (such as Python or C++), and you’re comfortable writing efficient, clean code. 4. You think critically, adapt quickly, and approach challenges with creativity and focus. 5. You’re passionate about learning, iterating, and continuously improving your skills and impact. 6. You enjoy working in close collaboration with others and thrive in environments where ideas are rigorously tested and debated. 7. Experience in applied research—especially in tech or finance—is a bonus. 8. While previous exposure to trading or crypto is helpful, it’s not a requirement. We value sharp thinkers who are eager to learn the domain. What You’ll Be Doing: 1. Designing and testing systematic trading strategies focused on digital assets. 2. Applying modern statistical and machine learning techniques to uncover market inefficiencies. 3. Exploring and evaluating new datasets to extract actionable signals. 4. Collaborating with other researchers and engineers to improve models and infrastructure. 5. Taking your research ideas from prototype to live deployment and receiving immediate feedback from real-world performance. 6. Contributing to the ongoing development of the research and trading platform. Why Join Us: 1. Work directly with experienced professionals from the forefront of quant finance and blockchain. 2. Be part of a flat, merit-based culture that values ideas, execution, and impact over titles. 3. See your work go live and deliver results in production—not in slides or whitepapers. 4. Grow rapidly alongside a high-caliber team in one of the most dynamic areas of finance.

Role :- Development and maintenance of the in-house C++ pricing libraries Advancing the quantitative toolbox by developing new technologies, algorithms and numerical techniques . Development and maintenance of multi-threaded servers for delivering data to users . Design, develop, test, and deploy elegant software solutions for automated trading systems. Design and build out model framework and signal research tools. Implement new signals and assets . Build execution and portfolio construction tools. Build tools and applications required by traders. You will work closely with the traders, quantitative analysts, compliance, and technology teams to provide innovative solutions with a focus on highly scalable systems. You will see your ideas and hard work used by experienced traders across a diverse range of instruments and markets. Requirements:- Excellent knowledge of both Python and C++. Experience with QuantLib library will be a major advantage for any candidate. Knowledge of fixed income and FX derivatives instruments and models will also be sought and interviews will centre around these areas . Strong foundational knowledge of computer science, mathematics & statistics. Financial experience/knowledge is a strong plus. Ideally you will have a Masters / PhD in a technical discipline (Computer Science, Engineering, Mathematics, Physics) A demonstrated track record in risk, quantitative or trading systems development. Apply:- Please send a PDF resume to quants@ekafinance.com

The Firm A well-capitalised, technology-driven trading firm operating at significant scale across digital assets, derivatives and prediction markets. The firm runs proprietary systematic strategies across multiple asset classes with institutional-grade infrastructure and deep liquidity. This role sits within a dedicated sports prediction markets trading desk — a high-priority growth area for the business — and represents an opportunity to join at an early and formative stage of its development. The Role A specialist quant trading position focused on market making in sports prediction contracts. Operating at the intersection of data analytics, probabilistic modelling and live sports markets, you will be responsible for systematically providing liquidity, managing risk and identifying pricing inefficiencies across a broad range of sports events. The role demands deep domain knowledge of both sports and prediction market dynamics, combined with rigorous quantitative and execution capability. Responsibilities 1. Systematically provide liquidity by posting buy and sell offers, managing spreads and facilitating efficient market operations across sports prediction contracts 2. Continuously monitor sports prediction markets — including soccer, basketball, baseball, football and emerging eSports — for price movements, liquidity shifts and volatility patterns 3. Monitor overall portfolio risk, position limits and exposure caps; adjust strategies in real time based on variance, probability shifts and new information 4. Conduct pre-market and post-market analysis of upcoming sporting events, identifying key pricing opportunities and tail risks 5. Place trades across multiple markets simultaneously, responding rapidly to changes in live odds, news flow and betting dynamics 6. Test and provide liquidity for new sports contracts as they are listed (BAU trading operations) 7. Analyse trade outcomes and refine predictive models for future events, including signal decay diagnostics and execution quality review 8. Collaborate with developers and risk managers to improve trading infrastructure, including connectivity, pricing engines, execution logic and booking systems 9. Prepare end-of-day performance summaries, risk reports and compliance documentation Requirements 1. Degree in Mathematics, Statistics, Economics, Finance, Computer Science or a related quantitative discipline; advanced degree is a strong advantage 2. 5+ years of profitable sports prediction trading experience on a leading trading desk, proprietary trading firm or market making environment 3. Deep understanding of sports prediction market mechanics, order flow dynamics, liquidity behaviour and pricing inefficiencies 4. Demonstrable track record of building, managing and improving live trading strategies in competitive prediction or sports markets 5. Strong probabilistic reasoning and statistical modelling skills; ability to translate real-time sporting data into actionable trading decisions 6. Proficient in Python; genuine interest in expanding technical skill set including automation and model integration 7. Experience with prediction market platforms, sports betting exchanges or similar financial environments 8. Highly organised, detail-oriented and able to manage multiple live positions simultaneously under pressure 9. Self-directed, adaptive and comfortable operating with significant autonomy in fast-paced, competitive environments What’s on Offer 1. Highly competitive base salary with a substantial performance-based compensation component — structured to reward genuine trading edge 2. Direct exposure to trading across multiple asset classes — including sports prediction markets, digital assets, derivatives and equities — within a single, institutionally scaled operation 3. A clear and meritocratic career trajectory — traders with a strong track record are given increasing autonomy, capital allocation and leadership responsibility 4. A collaborative, high-performance culture built around intellectual rigour, shared knowledge and continuous improvement 5. Access to cutting-edge proprietary technology, deep liquidity and a globally connected trading operation

The group researches, defines, and optimizes high-frequency trading strategies that leverage cutting-edge technology to improve speed and market access to improve their trades. Working closely with an experienced Quant Strategist, you can utilize your quantitative, research, analytical, and programming skills to gather, house, and analyze data to help optimize existing models. As your experience grows, you will be expected to contribute your own strategy ideas. This is an excellent opportunity to learn about multiple asset classes and high-frequency trading whilst leveraging your current computational skills. Responsibilities:- 1. Designing and developing systems built in C++ or Java 2. Utilizing quantitative, research, analytical, and programming skills to gather, house and analyze data 3. Contributing strategy ideas as experience grows 4. Learning about multiple asset classes and high-frequency trading Qualifications: Candidates for this opportunity will have a PhD from a top tier University in Computer Science or other quantitative field such as Signal Processing, Data Mining, Mathematics, Operations Research etc.. In addition to a stellar academic record, you will have a track record of professional quantitative or technology achievements. Ideally, you will have some research experience either in academia or in a research lab. Experience in the financial markets is a plus but not mandatory. A process-driven approach to problem-solving. Intellectual curiosity in quantitative finance. Compensation: £ Base + benefits

Key Responsibilities 1. Research and implement high-frequency trading strategies, leveraging deep knowledge of market microstructure 2. Analyze large-scale market data to uncover inefficiencies and design robust, data-driven models 3. Build and maintain simulation and backtesting tools aligned with real-world trading conditions 4. Write and optimize production-grade code for signal generation, execution logic, and infrastructure components 5. Collaborate across disciplines to ensure seamless integration of research and engineering efforts 6. Monitor strategy performance, adapt models to changing market conditions, and manage risk Requirements 1. Strong experience in high-frequency trading or systematic strategies within crypto or traditional markets 2. Advanced programming skills in Python , along with proficiency in at least one compiled language (Rust preferred , C++ or Go also welcome) 3. Deep understanding of market microstructure and the technical nuances of low-latency trading 4. Background in a quantitative discipline such as mathematics, statistics, physics, computer science, or engineering (MSc or PhD preferred) 5. Practical experience working with large datasets, real-time data pipelines, and cloud-based research environments 6. Familiarity with version control systems (Git), Linux/Unix environments, and containerization tools such as Docker 7. Strong problem-solving ability, high attention to detail, and a mindset geared toward continuous improvement Location This role is based in London . We believe in the power of close collaboration, and candidates should either be located in London or willing to relocate. Support for relocation is available.

Role Overview: The successful candidate will design, implement, and manage data-driven trading models across global macroeconomic assets. The position requires deep expertise in statistical and machine learning methodologies, alongside robust programming and data-handling capabilities. Applicants should bring a verifiable track record of high information ratio strategies deployed in real-market environments. Key Responsibilities: 1. Develop and deploy systematic trading models across macro asset classes, primarily using futures and foreign exchange instruments. 2. Apply advanced quantitative methods—including time-series modeling, econometric analysis, and machine learning—to uncover alpha-generating signals. 3. Conduct extensive backtesting and stress testing to evaluate performance robustness, execution latency, and risk-adjusted return characteristics. 4. Collaborate within a research-driven environment to enhance alpha models, portfolio construction techniques, and signal processing infrastructure. 5. Monitor and evolve deployed strategies to maintain performance amid shifting market regimes. Ideal Background: 1. Demonstrated experience in quantitative macro research or portfolio management, with a track record of alpha generation and strategy deployment. 2. Exposure to short- and medium-term systematic trading styles, ideally within timeframes of hours to two weeks. 3. Advanced academic training (PhD or MSc) in a quantitative discipline such as Financial Engineering, Applied Mathematics, Statistics, Computer Science, or Physics. 4. Strong coding proficiency in Python and/or C#, with working knowledge of SQL for data manipulation and extraction. 5. Eligible to work in the UK and able to operate effectively in a collaborative, research-intensive setting.

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

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

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)

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

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.

Role Profile

The successful candidate for the Engineer, Post Trade role, will be working with the Director Technical Delivery Solution and Delivery, will form part of a team building a complex, ground-up cloud-based critical market infrastructure service in a bold new venture for LSEG. This opening requires a candidate who takes great pride in delivering excellence with excellent logical and technical skills and a can-do attitude combined with a helpful mentality, and a wish to play a critical role in forming and growing a new business.

Key Responsibilities

A strong focus on engineering excellence and coding, adopting an open and hands-on approach to problem-solving and delivery. Engage deeply in technical design and implementation to ensure solutions are robust, scalable, and aligned with industry standards. Actively contribute to all stages of the product engineering life cycle-solutioning, design, coding, and testing-while promoting collaboration and transparency within the team to drive high-quality outcomes.

Demonstrate ownership and pride in work, proactively taking on new responsibilities aligned with product engineering needs. Embrace and apply LSEG engineering principles, diving deep technically to build with purpose and foster excellence within the team through open collaboration. Create an environment of engagement, challenge, and constructive questioning, ensuring trust and respect are maintained and a strong one-team mentality is upheld

Key Skills and Experience

Event driven microservices architecture

• Strong understanding of microservices design, including pitfalls and best practices.
• Knowledge of Domain-Driven Design (DDD) and event-driven architecture principles.
• Experience with containerization and orchestration using Docker and Kubernetes.
• Skilled in event-driven patterns for efficient and robust communication.
• Expertise in building and maintaining DevOps pipelines, ideally with GitLab.
• Proficient in shift-left testing using tools like JUnit, Cucumber, Gherkin, PACT, and Test Containers.
• Working knowledge of event/message brokers such as Kafka and MQ.

Advanced Java

• Strong experience in Object-Oriented Programming (OOP).
• Advanced knowledge of Java 17+ features and practical experience with Spring Boot.
• Skilled in developing RESTful services, including REST design principles, Swagger/OpenAPI, and Spring REST MVC.
• Proficient in building and delivering enterprise-grade Java applications.
• Hands-on experience with data structures, algorithms, concurrency, and multi-threading.

Database Management

• Strong SQL knowledge with experience in relational databases such as Postgres.
• Working knowledge of object storage solutions, e.g., AWS S3.
• Familiarity with database version control tools like Flyway and Liquibase.

Cloud Architecture

• Experience working with major public cloud platforms, preferably AWS.
• Hands-on use of cloud-based services such as AWS Aurora, MSK, S3, and IAM.
• Basic understanding of cloud networking concepts.

Blockchain Integration and Interoperability

• Understanding of blockchain fundamentals, including consensus mechanisms and smart contracts.
• Knowledge of interoperability protocols
• Experience integrating blockchain solutions with existing enterprise systems.
• Familiarity with cross-chain communication and bridging technologies.
• Awareness of security considerations in blockchain integration (e.g., cryptographic standards, key management).
• Knowledge of token standard and transaction lifecycle.

Agile Ways of Working

• Strong understanding and commitment to the ethos of agile working.
• Experience working within Scrum and Kanban frameworks.
• Active participation in sprint ceremonies, including Product Backlog Refinement.
• Proven collaboration with cross-functional teams in scaled agile environments.

Key Behaviours

• Delivery-focused: Committed to meeting deadlines and managing stakeholder expectations.
• Accountable: Takes ownership and responsibility for outcomes.
• Collaborative: Works effectively within cross-functional teams and fosters teamwork.
• Communicative: Champions clear, respectful, and constructive communication.
• Quality-driven: Maintains high standards in code quality, testing, and CI/CD practices.
• Adaptable & Innovative: Eager to learn, improve, and embrace new technologies.
• Critical yet Respectful: Challenges ideas constructively while maintaining professionalism.
• Engineering Mindset: Passionate about solving problems and minimizing complexity.

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.

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 are hiring a hands-on AI Engineer to own the design and delivery of a customer‑facing compiler and interface that allows users to performance financial markets analytics via natural language. Working as part of our Web team, the ideal candidate will hold working knowledge of LLMs and AI agents and some level of familiarity with web frameworks.

Responsibilities:

• Own the end‑to‑end design and implementation of a customer‑facing AI capability integrated into our trade surveillance platforms
• Build and evolve a multi‑layered AI agent capable of interpreting natural‑language user queries and consulting documentation to generate appropriate responses
• Ensure generated results are presented clearly to users as well as the reasoning behind decisions
• Integrate AWS Bedrock with our web backend to support LLM‑driven reasoning and workflows
• Develop frontend components to surface AI outputs, user prompts, and confirmation flows for AI‑initiated actions
• Work closely with cross-functional stakeholders e.g. product to ensure solutions are robust, explainable, secure and scalable

Requirements

• Full stack software engineering experience with a strong track record of building and owning complex, production systems
• Demonstrated experience designing and delivering AI‑powered features that solve real customer problems
• Deep familiarity with LLMs, AI agents and conversational systems, including their practical limitations
• Solid theoretical understanding of machine learning fundamentals, including neural networks and transformer architectures
• Experience with cloud‑based AI platforms such as AWS Bedrock is desirable
• Experience using AI‑assisted development tools (e.g. Copilot or similar) to improve engineering productivity

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.

We are seeking a talented Quantitative Developer to join an established and highly successful systematic Stat-Arb Equities team at a tier‑one hedge fund in London. This exciting position will be sat on the trading desk, reporting directly in to the Portfolio Manager, forming part of a highly hands‑on mid-frequency systematic stat‑arb equities team. You will use advanced techniques to enhance existing frameworks and drive further improvements in algorithmic trading performance.

Following several highly successful years, the team is expanding and looking for a technically strong quantitative developer who enjoys working closely with a trading team, seeks greater exposure to trading, and is motivated to help drive the ongoing development and enhancement of trading infrastructure and analytics.

You will work in a highly collaborative, research driven environment where quantitative developers are involved across the full quantitative lifecycle, including building research and backtesting tooling, implementing trading strategies, optimisation and continuous performance enhancement. This will be alongside working closely with senior members of the team who provide ongoing mentorship, technical guidance, and exposure to strategic decision‑making.

Key Responsibilities

• Design, build, and maintain research and production‑grade trading infrastructure for systematic equities strategies.
• Work closely with the Portfolio Manager and quantitative researchers to implement, optimise, and maintain stat‑arb equity strategies.
• Develop robust, efficient, and scalable Python and R codebases for research, backtesting, and live trading.
• Contribute to improving data pipelines, analytics frameworks, and monitoring tools within a Linux environment.
• Support strategy performance analysis, debugging, and ongoing enhancement of live models.
• Take ownership of code quality, testing, and performance in a fast‑moving trading environment.

Required Qualifications

• 2-5 years of experience in a Quantitative Developer, Software Engineer, or similar role.
• Strong hands‑on development experience working in a Linux environment.
• Advanced skills in Python.
• Solid experience with R.
• Strong software engineering fundamentals, including version control, testing, and production‑ready code.
• Excellent problem‑solving skills, attention to detail, and the ability to work independently in a high performance team.

Preferred Qualifications

• Familiarity with systematic equities strategies.
• Experience working closely with PMs or traders in a front‑office environment.
• Experience optimising research workflows, backtesting frameworks, or execution systems.
• Familiarity with large datasets, time‑series analysis, and quantitative performance diagnostics.
• Background in Computer Science, Engineering, Mathematics, Physics, or another quantitative discipline.

Discover your future at Citi
Working at Citi is far more than just a job. A career with us means joining a team of more than 230,000 dedicated people from around the globe. At Citi, you’ll have the opportunity to grow your career, give back to your community and make a real impact.

Job Overview
At Citi, we are pioneering the future of enterprise operations through innovative technology. Our COO-Technology Engineering and Architecture capability is at the forefront, responsible for architecting best-in-class solutions, driving end-to-end transformation, and integrating cutting-edge Generative AI solutions to unlock unparalleled efficiency, automation, and risk reduction across our global operations.

The Team: Innovating at Scale
Our team is a dynamic hub of engineers and innovators dedicated to solving complex business challenges with intelligent solutions. We believe in building robust, scalable products that deliver tangible impact. We foster an environment of continuous learning, rapid iteration, and strong engineering practices. Here, you’ll work alongside passionate experts, leverage the latest in AI, and contribute to a culture that values clean code, thoughtful design, and direct, hands-on problem-solving. We’re not just adopting AI; we’re building the intelligence that powers our enterprise.

The Role:
We are seeking an exceptional Staff Generative AI Engineer to join our team. This is a critical, deeply hands-on role for a seasoned software engineer with a profound passion for Generative AI, Large Language Models (LLMs), and agentic frameworks. You will be instrumental in designing, building, and deploying real-world, commercial production systems, not just proofs-of-concept.
This is an Individual Contributor (IC) role with no direct people management responsibilities.
Your expertise in containers (especially OpenShift), strong Python programming, and advanced LLM/agentic frameworks will be essential as you drive significant operational efficiencies and set new standards for engineering excellence. If you’re a builder who thrives on technical challenge, delivering measurable impact, and mentoring others while getting your hands dirty with code, we want to hear from you.
As a Staff Generative AI Engineer, you will:

• Architect & Build Production Systems: Lead the hands-on development of sophisticated Generative AI applications, LLM-powered solutions, and intricate agentic frameworks primarily using Python. Your code will be clean, performant, scalable, and deployed directly into commercial production environments, solving real business problems.
• Pioneer Automation with Agents: Design and implement intelligent agents capable of understanding, reasoning, and orchestrating complex workflows to automate critical enterprise business processes, driving efficiency and reducing operational risk at scale.
• Master Containerized Deployments: Demonstrate deep comfort and expertise with container technologies, particularly deploying and managing applications within OpenShift environments.
• Drive Technical Direction & Ownership: Contribute significantly to the technical strategy and roadmap for Generative AI adoption, influencing architectural decisions and technology choices across our product portfolio, ensuring all solutions are production-ready.
• Champion Engineering Excellence: Instill and uphold rigorous software engineering best practices, including robust testing, code reviews, documentation, and continuous integration/delivery, ensuring the highest quality for our mission-critical systems running in production.
• Innovate & Research: Stay at the bleeding edge of Generative AI, actively exploring new models, techniques, and frameworks. Contribute to both applied engineering and research initiatives within the domain. You will have access to state-of-the-art AI-assisted development tools like Devin and Copilot to amplify your productivity and creativity.
• Mentor & Collaborate: Act as a technical leader and mentor to junior engineers, fostering a culture of knowledge sharing and continuous improvement. Collaborate closely with cross-functional teams, product managers, and stakeholders to deliver impactful solutions.
• Iterate & Deliver: Thrive in an agile, fast-paced environment, prioritizing rapid delivery, iterative development, and adaptability. Focus on delivering measurable business value and learning quickly from prototypes and deployments, always with a path to production in mind.
• Ensure Responsible AI: Design and implement robust guardrails and ethical considerations into AI solutions, proactively assessing and mitigating risks in line with organizational and regulatory standards.

Minimum Qualifications:

• Proven professional software engineering experience, demonstrating a strong track record of designing, building, and delivering scalable enterprise-grade solutions in commercial production environments, not just proofs-of-concept.
• Expert-level proficiency in Python is a must-have, with a deep understanding of its ecosystem for AI/ML development, data engineering, and backend services. Full-stack development experience is a distinct advantage.
• Extensive hands-on experience with Generative AI concepts, Large Language Models (LLMs), transformer architectures, RAG, and advanced agentic frameworks (e.g., LangChain, LangGraph, Google ADK. Optionally AutoGen, CrewAI, LlamaIndex, Semantic Kernel).
• Deep comfort and practical experience with containers and orchestration technologies, specifically OpenShift.
• Demonstrated ability to architect, develop, and deploy highly performant, large-scale AI/ML systems into production environments.
• Strong understanding of modern software development principles, clean code practices, data structures, algorithms, and distributed systems.
• Proficiency with Relational (preferably, PostgreSQL) and Vector (preferably, pgvector) databases.

Preferred Qualifications (Bonus Points):

• Proficiency in additional programming languages such as Java, JavaScript/TypeScript, or Golang.
• Experience with specific frameworks like Spring (AI, Boot), N8N, or Flask.
• Familiarity with messaging and integration platforms such as Kafka or JMS/MQ.
• Experience with UI development using modern frameworks like React JS or StreamLit for interactive AI applications.
• Practical experience in model risk management, developing AI guardrails, and establishing end-user adoption pathways for Generative AI solutions.
• A proven track record of contributing to open-source projects or publishing relevant research in AI/ML.

Why You’ll Love Working Here:

• Unprecedented Impact & Visibility: Contribute to critical, high-visibility projects that are transforming a global enterprise, working on firm-wide initiatives that directly influence our operational future.
• Cutting-Edge Technology: Work with the latest Generative AI models, agentic frameworks, and cloud-native technologies, enhanced by access to AI-assisted development tools like Devin and Copilot.
• Growth & Development: A culture of continuous learning, mentorship, and opportunities to lead and innovate. Benefit from extensive learning resources including Udemy for Business and Pluralsight.
• Collaborative Environment: Join a highly skilled, passionate team that values collaboration, intellectual curiosity, and shared success.
• Flexible Work Environment: Embrace a hybrid working model, balancing productive in-office collaboration (3 days) with the flexibility of working from home (up to 2 days).
• Global Scale: Build solutions that operate at a massive scale, impacting users and operations worldwide.

Join us to build the future of intelligent enterprise solutions!

Job Family Group:
Technology ------------------------------------------------------
Job Family:
Systems & Engineering ------------------------------------------------------
Time Type:
Full time ------------------------------------------------------
Most Relevant Skills
Please see the requirements listed above.------------------------------------------------------
Other Relevant Skills
For complementary skills, please see above and/or contact the recruiter.------------------------------------------------------
Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.

If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi .

View Citi’s EEO Policy Statement and the Know Your Rights poster.

Role profile:

We are seeking a knowledgeable Quantitative Developer to join the Sustainable Index Research and Design team at FTSE Russell, a wholly owned subsidiary of the London Stock Exchange Group. The role reports directly to the Head of Sustainable Index Research and Design. The Sustainable Index Research & Design team is responsible for the development, design, and research of sustainable indices and related materials. The team works closely with both internal front- and back-office departments, as well as FTSE Russell’s partners and key clients, including major asset owners, fund managers, and investment banks, in the creation of new index products.

ROLE SUMMARY:

• We are seeking a Python Developer to join our team in developing scalable and efficient software solutions to support investment analytics and index construction.
• This role involves full lifecycle development, from design and implementation to continuous deployment, and close collaboration with quantitative researchers and product teams.
• The successful candidate will contribute to automating analytics, integrating research models, and enhancing performance and maintainability of our codebase.

WHAT YOU’LL BE DOING:

• Implement Python applications using object-oriented programming principles.
• Participate in the full software development lifecycle, including conceptualization, development, testing, and deployment.
• Analyse and optimize existing code for performance and maintainability.
• Work closely with quantitative researchers to integrate models and algorithms.
• Develop scalable, automated investment analytics and reporting tools.
• Collaborate to design and develop new index products.
• Respond to internal and external research queries related to index construction and analytics.

WHAT YOU’LL BRING:

• Bachelor’s or Master’s degree (or equivalent experience) in Computer Science, Engineering, Mathematics, or a related technical field.
• Strong Python programming skills with an emphasis on object-oriented design
• Experience using data analysis libraries such as pandas and numpy, and visualisation tools like Matplotlib or Plotly.
• Familiarity with version control (Git) and collaborative development workflows, and software testing principles and frameworks
• Ability to clearly communicate technical concepts within a multi-functional team.
• A proactive outlook with a willingness to learn and adapt in a fast-paced environment.
• Strong time management and the ability to handle fast turnarounds and shifting priorities.
• Ideally, a background or interest in financial markets, financial instruments, sustainable investment and investment analytics.

WHAT YOU’LL GET IN RETURN:

• A comprehensive compensation package that includes a competitive salary, performance-based bonuses, and a robust benefits programme.
• Opportunities for ongoing training and professional development, including access to workshops, seminars, and conferences to improve your skills and advance your career.
• A flexible work environment that supports a healthy work-life balance, including remote work options and generous paid time off.
• The opportunity to contribute to meaningful projects that drive sustainable investing practices, making a positive impact on the environment and society.
• A dynamic and inclusive workplace where diverse perspectives are valued, encouraging collaboration and innovation among team members.
• The chance to participate in our thought leadership initiatives, influencing industry discussions on sustainable investing.

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.

Lead Machine Learning Engineer Location : London Days in office : 2 days onsite Contract length : 6 months Contract engagement: inside IR35 We are looking for a Lead Machine Learning Engineer (SageMaker, MLOps, Explainability) to design, build, and productionise machine learning models that power our new matching platform. You will work across the full ML lifecycle - feature engineering, model development, training pipelines, deployment automation, inference optimisation, monitoring, and explainability. In this role, you will make strong hands-on technical contributions, take ownership of key components of the ML platform, and collaborate closely with data scientists, platform engineering, and product teams. You will help improve our MLOps practices, enhance observability, and ensure that our ML systems meet standards for security, performance, and compliance. This role is suited to an experienced engineer who can deliver production-grade ML systems, influence design decisions, and maintain high technical standards, while still working primarily as an individual contributor. Feature Engineering 1. Build and maintain scalable feature pipelines within data lakehouse architectures. 2. Develop fallback feature flows (e.g., export paths). 3. Implement robust data quality checks and contribute to the adoption of feature store patterns. Model Development & Scoring 1. Develop ranking, scoring, and entity-similarity models fit for the matching platform. 2. Implement calibrated confidence scores, thresholds, and model scoring logic. 3. Use modern ML Model frameworks such as PyTorch, TensorFlow, or XGBoost. 4. Collaborate with data scientists on model design and performance improvements. Explainability & Reason Codes • Apply SHAP or similar techniques to generate interpretable model explanations. • Produce reason codes suitable for business, operational, or regulatory consumption. • Ensure explainability outputs are versioned, tested, and integrated into inference workflows. ML Deployment & MLOps 1. Build and maintain training, processing, and inference pipelines using AWS SageMaker. 2. Integrate models with model registries and implement automated deployment patterns. 3. Support rollback and redeploy mechanisms for weight updates or model iterations. 4. Contribute to CI/CD improvements for ML-specific workflows. Inference Runtime & Cross-Account Serving 1. Deploy and optimise low-latency, real-time inference endpoints. 2. Implement secure AWS IAM patterns supporting cross-account inference access. 3. Build telemetry for request logging, performance tracking, and latency monitoring. 4. Solve runtime issues and optimise throughput and cost. Monitoring, Drift Detection & Telemetry 1. Implement feature drift and concept drift monitoring. 2. Build dashboards, alerts, and critical performance metrics to detect model degradation. 3. Develop telemetry and logging frameworks that respect data minimisation principles. Security, Compliance & ML Governance 1. Apply procedures for data handling, encryption, PII minimisation, and auditability. 2. Produce Model Cards, documentation, and lineage artefacts needed for governance. 3. Ensure that ML pipelines meet internal standards for reproducibility and traceability. Testing, Validation & Performance 1. Conduct validation of models using golden datasets, baseline tests, and regression testing. 2. Optimise models for latency-sensitive inference paths. 3. Support A/B tests, shadow deployments, and progressive rollout strategies. Essential 1. Strong experience delivering production ML systems end-to-end. 2. Proficiency with AWS SageMaker (training jobs, processing, endpoints, Model Registry). 3. Excellent Python skills and experience with ML Models such as PyTorch, TensorFlow, or XGBoost. 4. Hands-on experience with model explainability tools such as SHAP. 5. Understanding of low-latency, real-time inference patterns and optimisation techniques. 6. Experience implementing drift detection, monitoring, and telemetry. 7. Working knowledge of ML governance, data privacy, and secure ML practices. 8. Strong understanding of MLOps, CI/CD, and automation for ML workflows. Nice to Have 1. Experience working with feature stores or Lakehouse data architectures. 2. Previous experience with ranking, matching, or similarity models. 3. Familiarity with cross-account AWS IAM patterns and multi-account design. 4. Bachelors in a STEM subject, e.g. mathematics, physics, engineering, computer science, or adjacent 5. degrees.

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.