£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.

£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 £75,000 GBP

Performance Bonus

Hybrid WORKING

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

Senior Cyber Operations Analyst (Associate Manager)

Locations: London | Manchester | Bristol

Salary: Up to 75,000 + excellent package

Clearance: BPSS + SC clearance (or Eligible)

Are you an experienced Cyber Security Operations specialist looking to step into a senior role within a high-growth, high-impact cyber practice?

We’re supporting a top-tier consulting organisation (name anonymised) that is expanding its Blue Team and looking for a technical, curious and detail-driven Senior Cyber Operations Analyst to join their team.

This is a fantastic opportunity to work with cutting-edge tooling, contribute to threat-driven defensive security, and shape advanced SecOps capabilities across enterprise environments.

About the Role

As a Senior Cyber Operations Analyst at Associate Manager level, you’ll sit at the heart of a thriving Cyber Practice covering Assurance, Compliance, SecOps, Offensive Security and Research.

You’ll play a pivotal part in threat detection, incident response, detection engineering, and security monitoring - helping defend major UK organisations.

This role is perfect for someone who thrives in technical depth, enjoys problem-solving, and wants to contribute to a mission-driven cyber defence team.

Key Responsibilities

You will:

• Develop, maintain and enhance detection content (primarily for Splunk SIEM) across cloud, endpoint and network platforms
• Identify detection gaps, log ingestion issues and alert improvements
• Review and uplift existing SecOps standards, logging maturity, BAU monitoring and threat-led optimisation
• Perform day-to-day security monitoring, alert triage and incident response (9am-5:30pm rota)
• Investigate cyber security incidents and provide technical leadership during escalations
• Mentor junior analysts through shadowing and hands-on guidance
• Act as a technical SME during client engagements, including presenting to senior stakeholders
• Participate in alert testing, IR tabletop exercises, and readiness assessments
• Stay up to date with emerging intelligence, attacker behaviours and evolving threat landscapes

Additional (client-dependent) responsibilities may include:

• Proactive threat hunting
• Incident response playbook development
• Threat intelligence research
• Vulnerability scanning & reporting
• Internal (consultancy) and external (client-side) leadership opportunity

On-call requirement: approx. 1 week per month for high-priority incidents (additional compensation provided).

What We’re Looking For

Not every box needs to be ticked - but strong candidates will bring experience across areas such as:

• Threat intelligence models (Pyramid of Pain, IPCE, TI lifecycle)
• Detection engineering & alert development
• Scripting skills (Python, Bash, C/C++, Java)
• Core cybersecurity fundamentals: network, cloud, cryptography, forensics
• Understanding of attacker techniques, APT behaviours and network protocol abuse
• Familiarity with Windows/Linux investigation techniques

What’s in It for You

You’ll join an organisation that invests heavily in its people and offers:

• Competitive salary
• Private medical insurance
• 25 days annual leave
• 3 days paid charity leave
• Continuous learning & development opportunities
• Access to a cutting-edge cyber practice and diverse project portfolio
• Flexible working & mobility across multiple UK hubs

Security Clearance Requirement

This role requires eligibility for BPSS + SC clearance, which normally includes:

• 5 years continuous UK residency
• No periods of 30+ consecutive days outside the UK in that time
• British-only nationality (no dual citizenship) due to client conditions

Interested?

If you’re passionate about defensive security, thrive in technical SecOps work and want to make a measurable impact across major UK clients, we’d love to hear from you.

Apply directly or message me for a confidential chat.

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.

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 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

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.