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.

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.

£300k+ GBP

Onsite WORKING

Location: Central London, Greater London - United Kingdom Type: Permanent

Central Risk Book (CRB) Trader

Location: London or Geneva

Overview:

We are currently partnered with a well-established commodities firm to hire a Central Risk Book (CRB) Trader. This is a unique opportunity to join a high-performing trading environment with strong visibility across desks. While direct commodities experience is not essential, we are seeking candidates with robust futures trading experience and a proven track record in building and managing central risk books.

Key Responsibilities:

• Lead the design, development, and management of the Central Risk Book (CRB).
• Collaborate closely with centralized execution teams to manage risk and optimize returns.
• Work alongside technologists and quant developers to enhance execution algorithms
• Drive cross-desk visibility and strategic integration of risk across asset classes.
• Continuously refine models and execution strategies using data-driven insights.

Required Skills and Experience:

• Demonstrable success in building and managing CRBs or comparable centralized risk strategies.
• Strong experience in futures trading, preferably in a systematic or high-frequency context.
• Hands-on programming experience in at least one of: Python, SQL, C++, Java, or C#.
• Proven track record of systematic market making, ideally at higher frequencies.

To hear more details please apply to this position or contact Ben Mortimore at Anson McCade.

Job Reference: AMC/BMO/CRB01

Responsibilities

• Research and enhance equity factor models and portfolio construction techniques
• Design and prototype new systematic equity strategies and products
• Translate research into implementable signals within production platforms
• Partner with the portfolio engineering team on model implementation and execution
• Conduct standalone research leading to white papers and presentations
• Engage with distribution to articulate capabilities and support AUM growth
• Integrate systematic research into discretionary investment processes

Requirements

• Experience in quantitative equity, with a track record in equity factors and portfolio construction
• Deep knowledge of risk models, optimisation and sustainability integration
• Strong Python programming (pandas, NumPy) and data manipulation skills
• Proven ability to work with large datasets and research infrastructure
• Understanding of artificial intelligence (AI) and machine learning (ML) techniques applied to equity portfolios
• Postgraduate degree (MSc/PhD) in a quantitative discipline
• Evidence of published research or conference presentations is advantageous

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 commitment 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.

The Strat team is responsible for designing, building and maintaining the code that handles the data priming, the model execution and the post-processing of the solution into a format that clients can consume. The biggest component of the role is writing and testing code, which is written in python, so it is important to enjoy coding and be comfortable with designing and writing code in a large, shared codebase. Being comfortable with inter-library dependencies, python package management and continuous development practices is also crucial.

In addition to building the calculations, the Strat team is on the front-line when it comes to executing the multilateral optimization runs, which occur multiple times a week. This requires a high level of engagement with our Production team, to provide timely support during runs and help resolve issues as they arise in real time. A client-focused approach is therefore of paramount importance for the role. Successful candidates will build and support one or more of Quantile products. They work directly with our Production and Product Development teams to enhance the products based on feedback from clients and analysis of runs, as well as on strategic projects. We are looking for a junior quantitative developer to work on our optimisation services development and analytics.

Examples of recent projects include:

• Implement improvements to our IR LCH compression algorithm.
• Extend our LCH compression service suite extending it to FX product.
• Enhance our couterparty Risk optimisation with new constraints and features
• Enhance our support for hedge funds and clearing brokers in initial Margin optimisations
• Improve the runtime performance by reducing the data set and solution search space
• Improve data flow, minimising manual steps, avoiding task duplication, and building an event-driven architecture

Responsibilities:

• Develop enhancements to the service model libraries to add new features and/or improve others. This will be a mix of strategic projects (3-6 months) and shorter-term tactical changes

• Become familiar with the data flow and the run processes and continually strive to improve them

• Investigate how to tune the model to create desired outcomes for clients

• Support live runs

Essential:

• 2-5 years of professional experience building quantitative, data intensive products in python
• Excellent understanding of software development best practices (such as functional and OO paradigms and standard design patterns) and design principles (SOLID)
• Excellent understanding of commercial development practices such as testing, documentation, package management and SDLC
• Excellent understanding of python for numerical programs. In particular, pandas and numpy are a must
• Excellent problem-solving skills
• Strong communication skills (the role will involve explaining complex algorithms to colleagues with varying technical and mathematical experience)

Desirable

• Knowledge of UNIX & AWS
• Understanding of linear and mixed integer programming, and convex optimisation
• Experience with at least one commercial or open-source optimisation library or a mathematical modelling language
• Understanding of financial derivatives, margin and counterparty credit risk measures
• A solid mathematical background (numerical methods, linear algebra, partial differential equations, probability & statistics)

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.

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

A leading sports betting fund is seeking a Junior Quantitative Researcher to join its expanding quantitative research team. This is an exciting opportunity for an analytically minded individual with a passion for sports modelling, data science, and statistics to contribute to cutting-edge research and model development within a high-performing environment. Key Responsibilities 1. Assist senior quantitative researchers in delivering research and model development projects. 2. Support clients and internal teams by: 3. Developing, maintaining, and improving the mathematical libraries that power predictive models and analytical tools. 4. Building and maintaining software systems that deliver model outputs into production. 5. Perform statistical analysis of datasets, test hypotheses, and communicate findings effectively to key stakeholders. 6. Contribute to the ongoing enhancement of core programming libraries. 7. Participate in at least one professional development event annually—such as a conference, workshop, or networking event—focused on areas like sports analytics, statistics, machine learning, or gambling. Skills & Experience Required 1. MSc in Statistics , Data Science , Mathematics , or another quantitative discipline (e.g., Computer Science, Engineering, Finance) with a strong statistical component. 2. Prior experience in a role involving significant statistical analysis, demonstrating skills beyond academic study. 3. Programming experience and a willingness to learn and work in R . 4. Demonstrated passion for sports modelling—through personal projects, academic research, or independent analyses. 5. Commitment to continuous learning and professional growth. 6. Curiosity and enthusiasm for exploring new technologies and programming languages. 7. Eligibility to work in the UK . Preferred 1. Strong interest in horse racing , supported by prior modelling or data analysis projects. 2. Understanding of sports betting markets . 3. Familiarity with statistical and machine learning methods (e.g., GBM, Torch, CNN, LSTM, NLP, GNN). 4. Experience with additional programming languages (e.g., Python, C++, Julia). 5. Working knowledge of database systems (e.g., SQL, MongoDB, Redis, Postgres). 6. Experience with version control , code reviews , and merge requests . 7. Familiarity with CI/CD pipelines and test-driven development (TDD) .

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.

We’re seeking a Quantitative Researcher to join our London team and help develop cutting-edge signals, models, and trading strategies for global financial markets. You’ll work closely with a small group of researchers and engineers to design, implement, and evaluate components of our research infrastructure, applying rigorous statistical and computational methods. This is an opportunity to gain broad exposure across multiple areas of quantitative research and to rapidly deepen your expertise in quantitative finance within a collaborative, intellectually vibrant environment. What You’ll Do 1. Develop and test innovative signals, models, and strategies for systematic trading. 2. Design and implement research tools and data pipelines. 3. Evaluate model performance using advanced statistical techniques. 4. Collaborate with a small, high-performing team to generate new research ideas. What We’re Looking For 1. PhD (completed or near completion) or Postdoctoral researcher in Mathematics, Statistics, Machine Learning, Physics, Computer Science , or a related quantitative discipline. 2. Exceptional mathematical and analytical ability . 3. Strong programming skills in Python or C++. 4. Experience tackling data-intensive problems is a plus. 5. Proven ability to conduct applied mathematical or statistical research . 6. Success in mathematical competitions (e.g., IMO, Putnam) is advantageous. 7. Prior experience in a quantitative or trading environment is a plus. Who You Are 1. Intellectually curious, creative, and rigorous in your approach. 2. Eager to challenge assumptions and adapt in light of new evidence. 3. Highly motivated and accountable, with a strong sense of ownership. 4. Meticulous, detail-oriented, and capable of managing multiple priorities. 5. Collaborative and communicative, comfortable giving and receiving feedback. 6. Able to work effectively both independently and within a small team .

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)

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.

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.