Engineer the Quantum RevolutionYour expertise can help us shape the future of quantum computing at Oxford Ionics.

View Open Roles

Quantitative Trader - Execution Services.

Millennium Management
Greater London
3 weeks ago
Create job alert

Quantitative Trader - Execution Services

Job Specification: Quantitative Trader – Execution Services

Location: London – 20 GS

The Central Liquidity Strategies (CLS) business manages a range of portfolios and products designed to optimize the firm’s trading and execution approach by providing internal liquidity solutions for portfolio managers on both a risk and agency basis.

We are seeking a Quantitative Trader to assist with all aspects of running a systematic trading and internalization book. This is a hands-on role offering an entrepreneurial individual the opportunity to make an impact by managing one of the most unique risk books in Europe.

Your role will involve operating, developing, and driving excellence in the desk's suite of products, spanning the entire workflow—from liquidity provision to portfolio managers at various benchmarks, through portfolio management, to optimized sourcing of risk from the market.

As part of a small, highly collaborative global team, you will:

Operate and monitor the highly automated live trading system, ensuring excellent service by overseeing flows and performance, intervening when necessary.

Conduct quantitative research and development, analyzing large datasets, developing cutting-edge code, tools, and models, and leveraging large-scale compute infrastructure to optimize liquidity sourcing and provision both internally and externally.

Key Responsibilities:

Operate and enhance systematic trading workflows, ensuring high performance and reliability.

Provide liquidity solutions to portfolio managers and optimize risk sourcing from the market.

Analyze large datasets using a scientific approach to improve trading strategies and desk performance.

Develop and maintain tools, models, and infrastructure to support trading operations.

Collaborate with a global team to ensure seamless execution and service excellence.

Experience Required:

Candidates should have hands-on experience within a market-making, risk, or trading business, ideally in cash equities, and familiarity with the following concepts and techniques:

Portfolio risk measurement and modeling.

Toxicity profiling and alpha forecasting.

Automation, tooling, and maintaining data integrity/pipelines.

Market impact modeling.

Liquidity provision and market-making workflows, ideally in cash equities.

Portfolio construction and optimization.

Alpha combination and attribution.

Statistical metrics and dimensionality reduction.

PnL decomposition and explanation.

Technical Skillset Required:

Education: Degree in Computer Science, Physics, Engineering, Statistics, Applied Mathematics, or a related technical field; Master’s or Ph.D. preferred.

Programming: At least 4 years of professional experience with Python and/or KDB; experience with Java/C++ is beneficial.

Systems: High proficiency with Linux, Git, and CI toolsets.

Quantitative Skills: Strong grounding in statistical reasoning and standard machine learning techniques.

Learning Aptitude: Excellent ability to rapidly learn from both experience and academic literature in a dynamic, fast-paced environment.

Related Jobs

View all jobs

Quantitative Trader

Quantitative Trader

Quantitative Trader

Quantitative Trader - Execution Services.

Quantitative Risk & Data Analyst

Quantitative Developer

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Seasonal Hiring Peaks for Data Science Jobs: The Best Months to Apply & Why

The UK's data science sector has matured into one of Europe's most intellectually rewarding and financially attractive technology markets, with roles spanning from junior data analysts to principal data scientists and heads of artificial intelligence. With data science positions commanding salaries from £30,000 for graduate data analysts to £140,000+ for senior principal scientists, understanding when organisations actively recruit can dramatically accelerate your career progression in this intellectually stimulating and rapidly evolving field. Unlike traditional analytical roles, data science hiring follows distinct patterns influenced by business intelligence cycles, research funding schedules, and machine learning project timelines. The sector's unique combination of mathematical rigour, business impact requirements, and cutting-edge technology adoption creates predictable hiring windows that strategic professionals can leverage to advance their careers in extracting insights from tomorrow's data. This comprehensive guide explores the optimal timing for data science job applications in the UK, examining how enterprise analytics strategies, academic research cycles, and artificial intelligence initiatives influence recruitment patterns, and why strategic timing can determine whether you join a pioneering AI research team or miss the opportunity to develop the next generation of intelligent systems.

Pre-Employment Checks for Data Science Jobs: DBS, References & Right-to-Work and more Explained

Pre-employment screening in data science reflects the discipline's unique position at the intersection of statistical analysis, machine learning innovation, and strategic business intelligence. Data scientists often have privileged access to comprehensive datasets, proprietary algorithms, and business-critical insights that form the foundation of organisational strategy and competitive positioning. The data science industry operates within complex regulatory frameworks spanning GDPR, sector-specific data protection requirements, and emerging AI governance regulations. Data scientists must demonstrate not only technical competence in statistical modelling and machine learning but also deep understanding of research ethics, data privacy principles, and the societal implications of algorithmic decision-making. Modern data science roles frequently involve analysing personally identifiable information, financial data, healthcare records, and sensitive business intelligence across multiple jurisdictions and regulatory frameworks simultaneously. The combination of analytical privilege, predictive capabilities, and strategic influence makes thorough candidate verification essential for maintaining compliance, security, and public trust in data-driven insights and automated systems.

Why Now Is the Perfect Time to Launch Your Career in Data Science: The UK's Analytics Revolution

The United Kingdom stands at the forefront of a data science revolution that's reshaping how businesses make decisions, governments craft policies, and society tackles its greatest challenges. From the machine learning algorithms powering London's fintech innovation to the predictive models guiding Manchester's smart city initiatives, Britain's transformation into a data-driven economy has created an unprecedented demand for skilled data scientists that far outstrips the available talent. If you've been contemplating a career transition or seeking to position yourself at the cutting edge of the digital economy, data science represents one of the most intellectually stimulating, financially rewarding, and socially impactful career paths available today. The convergence of big data maturation, artificial intelligence mainstream adoption, business intelligence evolution, and cross-industry digital transformation has created the perfect conditions for data science career success.