£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

Artificial Intelligence Engineer McCabe & Barton London Area, United Kingdom (Hybrid) Save Apply AI Engineer - Agentic AI & LLM Solutions Leading Investment House | London/Hybrid | Contract | Competitive Day Rate About the Opportunity We are seeking an experiencedAI Engineer to join a leading global investment house embarking on an ambitiousAI transformation programme . This is a high-impact contract role focused on buildingend-to-end agentic AI and LLM-based solutions that solve real business problems across trading, operations, research, and front-office functions. You'll work directly with business stakeholders to understand workflows, design intelligent automation solutions, and rapidly prototype working AI systems that deliver measurable value. Key Responsibilities: AI Solution Design & Delivery 1. Buildend-to-end agentic AI and LLM-based solutions from concept to deployment 2. Design AI architectures that map toreal business problems in investment banking 3. Rapidly prototype and iterate AI solutions based on stakeholder feedback 4. Move quickly from business brief to working solution - velocity is critical 5. Own delivery independently with minimal supervision Business Engagement & Requirements: 1. Engage directly withbusiness stakeholders (traders, analysts, operations, research teams) to understand workflows and pain points 2. Translate business requirements intoAI solution designs 3. Demonstrate AI capabilities and educate stakeholders on art-of-the-possible 4. Gather feedback and iterate solutions based on real user needs 5. Communicate technical concepts to non-technical business audiences Technical Implementation: 1. Develop robustPython-based AI applications and agent systems 2. Integrate LLM capabilities (OpenAI, Anthropic, Azure OpenAI) into business workflows 3. Build agentic AI systems that can reason, plan, and execute multi-step tasks 4. Implement RAG (Retrieval-Augmented Generation) pipelines for domain-specific knowledge 5. Work with vector databases and enterprise data sources 6. Integrate AI solutions with existing .NET/C# enterprise systems where required Innovation & Best Practices 1. Stay current with rapidly evolving LLM and agentic AI landscape 2. Recommend appropriate AI frameworks and tools for different use cases 3. Establish best practices for responsible AI deployment in regulated environment 4. Balance innovation speed with security and compliance requirements Essential Skills & Experience AI & LLM Expertise 1. Proven experience building end-to-end agentic AI or LLM-based solutions in production environments 2. Deep understanding ofLLM capabilities and limitations - knows when AI is (and isn't) the right solution 3. Experience designingAI solutions that map to real business problems , not just technical demos or proof-of-concepts 4. Track record ofdelivering working AI solutions that create business value Technical Skills 1. Strong Python development skills - production-quality code, not just notebooks 2. Ability to architect and buildcomplete AI applications end-to-end 3. Experience integrating AI capabilities into existing enterprise systems 4. Understanding ofsoftware engineering best practices for AI systems Desirable Skills & Experience LLM & AI Frameworks 1. Experience with specificLLM providers (OpenAI, Anthropic, Azure OpenAI) 2. Familiarity withagent frameworks such as LangChain, LlamaIndex, AutoGen, or similar 3. Experience buildingmulti-agent systems and orchestration workflows 4. Knowledge ofprompt engineering and optimization techniques Technical Depth 1. C# / .NET background for enterprise integration in financial services 2. Experience withRAG pipelines and vector databases (Pinecone, Weaviate, ChromaDB, etc.) 3. Understanding ofembedding models and semantic search 4. Knowledge offine-tuning and model customization approaches

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

Head of Machine Learning Modeling

A global quantitative trading organization built around engineering excellence, scientific thinking, and fully automated trading.

Our teams create everything in-house—from the research infrastructure to the algorithms that run live in markets around the world.

We trade a wide mix of products, including equities, derivatives, options, commodities, rates, and crypto using both high-frequency and mid-frequency strategies.

Our dedicated team members are located across multiple continents, and while we maintain physical offices, our workflow is currently designed for a remote environment.

About the Role

We’re hiring an experienced ML leader to guide the next generation of predictive modeling that powers our research and trading systems. In this role, you’ll own the strategy, design, and execution of our modeling framework—from architecture choices to validation standards to production governance.

You’ll collaborate closely with quant researchers, data specialists, engineers, and traders to turn cutting-edge research into reliable, high-performance models used in live trading.

Responsibilities

You’ll be responsible for one of the most critical layers of our research platform—the modeling engine that feeds our trading systems. Your work will influence how we research, validate, and deploy ML-driven signals across the firm.

• Setting the long-term vision for our model portfolio, covering everything from boosted trees to time-series deep learning, graph-based models, and advanced architectures for order-book prediction.
• Designing training pipelines that enforce strict data hygiene—rolling and walk-forward validation, target construction, and leakage-free workflows.
• Building explainability and diagnostic tooling (SHAP, permutation tests, model dissection techniques) to understand model behavior.
• Developing ensemble strategies and regime-aware model routing.
• Leading and mentoring a team of ML researchers, shaping best practices for experimentation and documentation.
• Partnering with engineering and trading teams to ensure smooth deployment of models into live trading systems.

Requirements/Core Experience

• 5+ years working with machine learning, with at least 2 years applying ML in quantitative finance/investments/trading
• In depth knowledge of modern ML methods and architectures.
• Strong statistical foundation—comfortable with hypothesis testing, bootstrapping, time-series quirks, and related methods.
• Experience building ML systems that operate in real-time or near-real-time environments.
• Strong command of alpha evaluation (IC, rank correlations, stability, decay).
• Proficiency in Python and the scientific/ML ecosystem (NumPy, Pandas, PyTorch/TensorFlow).
• Understanding of market microstructure, order flow, order-book dynamics, and factor behavior is a major plus
• Experience guiding technical teams and shaping modeling direction.

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.

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
Engineer the future of global finance. At Citi, our Tech team doesn’t just support finance - we are helping to redefine it. Every day, $5 trillion crosses through our network. We do business in 180+ countries operating at a scale few can match. From deploying advanced AI to helping shape global markets, we build systems that matter. Look to join a team where your work helps influence economies, your ideas can drive innovation and outcomes, and your growth is backed by mentorship, continuous learning and flexibility with potential hybrid work opportunities. Help solve real-world challenges that touch millions and get the opportunity to build the future of finance with Citi Tech.
By Joining Citi, you will become part of a global organisation whose mission is to serve as a trusted partner to our clients by responsibly providing financial services that enable growth and economic progress.

Citi is seeking a highly motivated candidate for Python lead 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 Responsibilities:

• Research and resolve complex issues, escalating as appropriate.
• 8+ 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

What we can offer you
We work hard to have a positive financial and social impact on the communities we serve. In turn, we put our employees first and provide the best-in-class benefits they need to be well, live well and save well.

By joining Citi, you will not only be part of a business casual workplace with a hybrid working model (up to 2 days working at home per week), but also receive a competitive base salary (which is annually reviewed), and enjoy a whole host of additional benefits such as:

• Generous holiday allowance starting at 27 days plus bank holidays; increasing with tenure
• A discretional annual performance related bonus
• Private medical insurance packages to suit your personal circumstances
• Employee Assistance Program
• Pension Plan
• Paid Parental Leave
• Special discounts for employees, family, and friends
• Access to an array of learning and development resources

Alongside these benefits Citi is committed to ensuring our workplace is where everyone feels comfortable coming to work as their whole self every day. We want the best talent around the world to be energized to join us, motivated to stay, and empowered to thrive.

Sounds like Citi has everything you need? Then apply to discover the true extent of your capabilities.

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

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

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

Role:- 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

You’ll be developing components for a research and trading platform used by quant researchers and portfolio managers, handling data from a wide range of sources, and optimizing performance for simulation and live execution. Python is the primary language used throughout the stack, making strong fluency essential. Core Responsibilities 1. Contribute to the architecture, testing, and performance tuning of a scalable trading and backtesting platform. 2. Build reliable, production-grade tools that enable researchers to access, clean, and analyze market and alternative data. 3. Collaborate with engineers and quantitative researchers to support model development and operational workflows. 4. Investigate and resolve software issues in live and simulation environments; contribute to code quality and robustness. What We’re Looking For 1. 1–3+ years of professional Python development experience (finance background not required). 2. Solid engineering mindset with an ability to design clean, modular code for long-term maintainability. 3. Comfortable working with relational databases; experience with data pipelines is a plus. 4. Clear communication skills and the ability to contribute to a collaborative, fast-paced team environment. 5. Strong academic background in a STEM subject from a leading university. Bonus Points 1. Familiarity with cloud-native technologies (e.g. AWS, GCP) and containerized environments. 2. Exposure to CI/CD workflows or DevOps practices. 3. Enthusiasm for test-driven development and clean deployment processes. 4. A genuine interest in quantitative finance or systematic trading systems. 5. Eligibility to work in the UK is required. If you’re a Python developer who enjoys solving complex problems with real-world impact—and wants to learn about quantitative trading in the process—this role offers a front-row seat.

Role:- This team member will be responsible for the implementation of technology to enable large-scale computational efforts in quantitative research, as well as related efforts, such as the preparation and transformation of data and other operational tasks. This role will work with senior technologists on the design and implementation of systems, and work closely with the quantitative research team to enable their mission You will:- Partner closely with the Senior Portfolio Manager to develop data engineering and prediction tools primarily for the systematic trading of equities Develop software engineering solutions for quantitative research and trading Assist in designing, coding, and maintaining tools for the systematic trading infrastructure of the team Build and maintain robust data pipelines and databases that ingest and transform large amounts of data Develop processes that validate the integrity of the data Implementation and operation of systems to enable quantitative research (i.e. large scale computation and serialization frameworks) Requirements :- Master’s or PhD in Computer Science, Physics, Engineering, Statistics, Applied Mathematics, or related technical field appropriate to a computational background Expert in C++ Advanced programming skills in Python Strong Linux-based development Knowledge of machine learning and statistical techniques and related libraries Experience as a quantitative developer supporting an intraday (or faster) system ( 3 years experience at least) Experience with the development practices of large tech (Google/Meta, etc.) or finance firms Experience with financial data Approx. 3-4 years of professional experience in a computer science/computational role Experience working in a technical environment with DevOps functions (Google Cloud, Airflow, Influx DB, Grafana) 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.