£75,000 GBP

Onsite WORKING

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

Quantitative Analyst

We are partnered with a market-leading, globally renowned investment firm seeking to hire a Desk Quant Analyst. The firm designs and builds its own proprietary systems to deliver strong, consistent returns for its clients. With deep expertise in trading operations, collaboration is embedded into its global culture, enabling technology, research, and operations teams to work seamlessly across regions. Driven by a commitment to high-quality performance, the firm leads the industry in technology- and data-driven quantitative strategies across global financial markets.

Key responsibilities as a Quantitative Analyst

• Handling and improving the codebase of strategies within our clients trading network.
• Handle large data sets used in the production and research environments.
• Conduct monitoring tasks on trading activities.
• Work in collaboration with quant researchers and traders to manage the changing needs of the trading desks.

Qualifications needed for a Quantitative Analyst

• Bachelors degree in engineering, computer science or another technical related subject.
• programming proficiency with at least one major programming or scripting language (e.g. C++, Java, Python)
• high level of communication skills and ability to work efficiently with colleagues across multiple areas

Additional desirable Qualifications for Quantitative analyst

• Knowledge of Q/KDB+
• Knowledge of Linux and Bash
• Further quantitative skills

If you are interested, then please apply.

£Up to £65,000 GBP

Competitive Bonus

Hybrid WORKING

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

Machine Learning Engineer

Join a high-impact AI and data science consultancy recognised for delivering exceptional outcomes across National Security, Defence, Space, and government sectors. This is a unique opportunity to work on cutting-edge AI and machine learning projects that make a tangible difference in the UK, supporting critical national security initiatives.

As a Machine Learning Engineer, you will design, develop, and deploy machine learning models that address some of the most complex challenges in national security. You will work in a consultative, hands-on role, collaborating with data scientists, software engineers, product managers, and stakeholders across the full lifecycle, from hypothesis through to production deployment.

Due to the sensitive nature of this work, candidates must be willing to undergo DV (Developed Vetting) security clearance, be sole British nationals, and have not spent more than 29 consecutive days outside the UK in the last 5 years. Please note that this role does not provide visa sponsorship and is not open to applicants on Skilled Worker or Dependent visas.

This role offers the opportunity to deliver real-world impact, working with diverse data types - including text, images, audio, video, and geospatial data - while applying cutting-edge methods in AI, machine learning, and MLOps/LLMOps practices.

You’ll have the opportunity to:

• Work alongside leading data scientists, ML engineers, and AI researchers on national security projects
• Design, develop, and iterate on machine learning models for traditional ML use cases and GenAI/LLM applications
• Explore and implement ML and LLM models on complex, multi-modal datasets
• Apply modern MLOps/LLMOps practices, including experiment tracking, versioning, and deployment on cloud platforms
• Influence technical direction and best practice in ML and AI engineering
• Mentor and support junior engineers and graduates
• Engage directly with clients to scope, design, and deliver operationally-ready AI and ML solutions

Key Responsibilities:

• Design, develop, and deploy machine learning models for forecasting, classification, anomaly detection, and LLM applications
• Lead experimentation cycles: define hypotheses, design experiments, evaluate results, and iterate rapidly
• Transition validated experiments into production-ready solutions, working closely with other engineers on deployment and monitoring
• Build and optimise ML pipelines using cloud-based platforms and experiment tracking tools
• Implement robust experiment tracking, model versioning, and reproducibility practices with full audit trails
• Support production models through monitoring, performance analysis, and continuous improvement
• Apply responsible AI practices, including model explainability, fairness, and ethical considerations
• Present experiment findings and production outcomes to stakeholders, articulating operational and strategic value
• Mentor junior colleagues and share learnings across the team

Key Requirements:

• Willingness to undergo DV (Developed Vetting) security clearance
• Sole British national with no more than 29 consecutive days outside the UK in the last 5 years
• Proven experience as a Machine Learning Engineer or equivalent role
• Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow
• Strong experience with cloud-based ML deployment (e.g., AWS SageMaker, Lambda, S3)
• Knowledge of MLOps/LLMOps tooling (e.g., MLflow, Weights & Biases, Data Version Control)
• Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures
• Ability to absorb complex scientific and technical concepts and apply them to operational solutions
• Strong communication skills for both technical and non-technical stakeholders
• Curiosity, adaptability, and a desire to deliver real-world impact

You will gain exposure to:

• Advanced ML and LLM methods applied to national security challenges
• Deployment of ML models at scale using cloud platforms and MLOps/LLMOps pipelines
• A broad range of data types, including text, images, audio, video, and geospatial data
• Ethical, privacy, and security considerations in AI/ML applications
• High-impact projects with government and defence clients
• Mentorship and development opportunities within a diverse, innovative environment

Why Join:

• Work on high-impact projects that directly support national security
• Gain deep exposure to cutting-edge ML, LLM, and AI technologies
• Accelerate your career in a supportive, high-performance consultancy
• Be part of a culture that values innovation, collaboration, and engineering excellence

Interested? Apply Now!

£150,000-250,000 GBP

Formulaic Bonus

Onsite WORKING

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

Our client is an established quantitative hedge fund operating in the mid/low frequency trading space, with teams globally. The firm is looking for experienced Quantitative Researchers/Traders and Portfolio Managers, particularly those covering systematic Macro Futures or FICC markets, to build and lead a team and trade their own strategies in return for a performance based bonus.

The firm can offer exceptional resources, including historical market data, alternative/fundamental datasets, development support, and cutting-edge execution infrastructure, allowing strategies to cover intraday and mid frequency time horizons, while maintaining low costs and a quick time to market.

The Role:

• Building and leading a desk where you will research and trade alphas based on analysis of market or alternative data.
• Researching and monetizing signals, monitoring performance of models and optimising them where possible.
• Creating quantitative tools to aid the strategy development process, such as execution algorithms, modelling libraries, etc. for the rest of your trading team to use.

Requirements:

• A degree from a prestigious university in a numerate field. Previous successful candidates have degrees in Engineering, Physics, Mathematics, Computer Science, etc.
• Coding proficiency in at least one language, such as C++ or Python.
• At least three years of experience as a Quantitative Researcher/Trader, where you used sophisticated quant methods for the research and optimisation of macro strategies.
• You will need to be a confident, resilient, and highly motivated individual, capable of working collaboratively with your colleagues in your office and in other locations.

£120,000 GBP

+Sign on +EOY Bonus

Onsite WORKING

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

About the Company:

Our client is seeking a talented Quantitative Researcher to join their team and contribute to the development of cutting-edge trading strategies within their automated trading framework.

Key Responsibilities:

• Research and implement algorithmic trading strategies.
• Analyze large data sets using advanced statistical and quantitative techniques to identify trading opportunities.
• Develop a deep understanding of market structure across various exchanges and asset classes.

Qualifications and Skills:

• Strong quantitative background (Mathematics, Statistics, Econometrics, Financial Engineering, Operations Research, Computer Science, or Physics).
• Proficiency in at least one programming or scripting language (e.g., Python, C++, Java).
• Excellent communication skills.
• Capable of working effectively under pressure in a fast-paced environment.

£150k+ GBP

Onsite WORKING

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

Quant Developer - Equities

Location: London or Dubai

Permanent

Our client are a market leading hedge fund, with a global reach in relation to their clients and offices. They are on the lookout for a talented Quant Developer with exceptional skills in python programming, and solid experience on equities focused projects

Responsibilities for an Equity Derivatives Quant:
• Core Trading Engine Development: Build, maintain, and enhance the core trading engine to support optimal performance.
• Systematic Trade Automations: Create and implement automated trading systems to improve efficiency and drive results.
• Collaborative Innovation: Partner with traders, researchers, and developers to understand needs and deliver tailored solutions.

Requirements for an Equity Derivatives Quant:
• Educational Background: Bachelor’s or Master’s degree in Computer Science, Mathematics, Physics, Engineering, or a related field
• Extensive knowledge surrounding equities asset class
• At least 2 years experience within the financial services industry
• Hands on experience with object orientated programming, using Python
• Strong communication skills and confidence in working within a collaborative team environment.

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

Job Reference: AMC/BMO/QD01

£150,000-200,000 GBP

• Performance based bonus

Onsite WORKING

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

Quant Researcher/Trader - Crypto - London/Paris

Anson McCade are working with a systematic hedge fund which is expanding their Crypto team. The firm can hire globally, and is looking for a Quant Researcher/Trader to research and deploy either HFT/MM strategies. The successful candidate will be able to manage their own models, and will receive a performance-based bonus.

The Role:

• Researching strategies across CeFi or DeFi venues in collaboration with other Quantitative Researchers, Developers and the Research Lead.
• Working on the development of infrastructure and tools, as well as the research, implementation and management of strategies.
• The successful candidate will manage their own book, and can lead more junior Quants in the team.

Requirements:

• The ideal candidate will have over 2 years of experience, including a background in Market Making or Central Risk Book trading. Experience with digital assets is preferred but not required.
• Coding skills in Python, experience with other programming languages is also beneficial.
• A Master’s or PhD from a top university is preferred.

£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