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.

Role:- The role involves many things such as:- 1. Contribute to the development of thetechnology and automation of routine tasks. 2. Improve execution/alphas through backtesting/analysis 3. Assist in the deployment and verification of upgrades to the production environment’s technical infrastructure, custom trading applications, market data distribution plant, etc. 4. Onboard and organise new data sets. 5. Help launch new strategies and model. 6. Learn, try and implement new technologies (we love open source). 7. Proactively deal with monitoring alerts and help develop the monitoring platform. 8. Provide support for issues. 9. Design and implement trading infrastructure, build data analytics tools or develop real-time execution strategies. 10. Work on complex computational and data related problems. Implement efficient and innovative solutions 11. Build tools and engine that enhance our ability to analyse data and contribute to improve workflow. 12. Support post-trade activities to aid effective clearing and accurate record-keeping. 13. Development and maintenance of all systems, including Linux servers and desktops, databases, storage solutions, etc. Requirements:- 1. Significant programming experience is a must, as is a genuine passion for solving complex problems through programming. 2. You enjoy coding, rather than considering it just a tool, but want your code to have real world results and effects. 3. You know about data structures and algorithms, and can practically apply the knowledge to real world problems. 4. You have strong communication skills and a simple, down-to-earth style when articulating your ideas. 5. You’re self-directed and can effectively and independently manage your time across various projects. 6. You’re honest, reliable and take pride in your work. 7. You’re enthusiastic, driven to develop your skills and open to new ideas 8. You’re flexible, adaptable and can jump from individual contributor to collaborative team member. 9. Work is conducted in a Linux environment, mainly in C++ and Python, and embraces grid computing. Skills and knowledge here would be very helpful, but not essential. Ideally you will have a strong undergraduate degree in a numerate discipline from a top-tier university. Apply:- Please contact Sara Hunter at quants@ekafinance.com

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 .

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
The Applications Development Intermediate Programmer Analyst is an intermediate level position responsible for participation in the establishment and implementation of new or revised application systems and programs in coordination with the Technology team. The overall objective of this role is to contribute to applications systems analysis and programming activities.

Citi is seeking a highly motivated candidate for Python developer in Wholesale Credit Risk Technology team that serves Institutional Credit Management (ICM). We are looking for a talented professional with a solid technical acumen to partner with onshore and offshore teams and design and deliver innovative technology solution for the front office, Credit Risk Business. The candidate will be a core member of the technology team responsible implementing projects based on Python, FastAPI , MCP, LLM, Java and using latest technologies. Excellent opportunity to immerse in and learn within the Wholesale Credit Risk Division and gain exposure to business and technology initiatives targeted to maintain lead position among its competitors.

Job requirements

• Research and resolve complex issues, escalating as appropriate.
• 3+ years of hands on experience in building an enterprise scale highly componentized application using Python, FastAPI
• Hands on development experience in Python
• Experience working with CI/CD pipelines, Kubernetes and other containerized platforms.
• Ability to effectively interact, collaborate with development team
• Ability to effectively communicate development progress to the Project Lead
• Work with developers onshore, offshore and matrix teams to implement a business solution
• Investigate possible bug scenarios and production support issues
• Recent experience with modern Python Development using Large Language models, Model Context Protocol, & Retrieval Augmented Generation (RAG) architecture
• Experience developing application in Financial Services industry is preferred

Education:

• Bachelor’s degree/University degree or equivalent experience

This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.

Job Family Group:
Technology ------------------------------------------------------
Job Family:
Applications Development ------------------------------------------------------
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.