Top London Quantitative Analyst Jobs

The Quantitative Research Analyst Intern will develop models, implement trading strategies, and conduct statistical analysis during an 11-week program.

Develop and improve quantitative models for investment strategies, conduct statistical analysis, and implement trading models. Requires strong analytical skills and relevant degree.

Off-cycle quantitative research intern supporting systematic trading, financial engineering, statistical modeling, portfolio optimization, and derivatives pricing. Responsibilities include developing mathematical models and algorithms, valuing and hedging transactions, conducting alpha research, calibrating models, optimizing pricing, managing portfolio risk, and collaborating with traders, technologists, sales, and risk teams. Candidates gain hands-on global markets experience and may be considered for full-time employment after successful completion.

Develop and validate quantitative models and algorithms for risk and treasury operations. Responsibilities include data analysis, backtesting, model assessment, software and tool enhancement, financial optimization, and collaboration with internal teams. The role involves applying academic quantitative knowledge to banking, financial instruments, and global markets while proposing solutions to complex modeling challenges.

Supports quantitative risk and treasury research by analyzing data, backtesting strategies, maintaining software tools, evaluating model soundness, and developing, validating, and enhancing mathematical models and algorithms for financial applications.

Design, build, deploy, and operate systematic interest rate swaps trading systems covering pricing, risk projection, hedging, and execution. Develop research infrastructure, backtesting and simulation tools, quantitative models, signal pipelines, and analytics over large datasets. Analyze trading data, improve strategies, support live trading, resolve incidents, and enhance monitoring and controls.

Develop and maintain pricing and risk models and quantitative libraries for FX options. Design algorithms, APIs, risk frameworks, testing processes, and pricing engines using C++ and Python. Collaborate with traders, sales, risk teams, and international quant groups to explain model assumptions, support products, and improve quantitative tools. The role requires advanced knowledge of FX valuation, options pricing, probability, stochastic processes, and quantitative modeling.

Conduct quantitative research across equities, derivatives, and multi-asset strategies; develop proprietary datasets, signals, models, and production pipelines; perform robust backtesting and validation; publish actionable investment insights; and provide high-touch service to institutional clients.

Develop quantitative models, analytical tools, and portfolio frameworks supporting strategic asset allocation, reference portfolio design, portfolio construction, and risk analysis. Conduct portfolio optimisation, scenario analysis, robustness testing, and sensitivity analysis across multi-asset portfolios. Translate complex quantitative findings into clear investment insights, evaluate model limitations, and apply practical investment judgment. Maintain reliable Python-based tools with appropriate testing, documentation, and version control while collaborating with investment and quantitative portfolio design teams.

Develop and support valuation models for convertible bonds and other asset classes within a product development team. Responsibilities include idea generation, product specifications, UI design, manual and automated QA, client-requested feature delivery, and collaboration with quantitative developers. The role provides training in financial markets, convertible bond structures, pricing models, and front-to-back capital markets processes, with potential progression into dedicated quantitative development.

Develop, enhance, and validate quantitative risk models for derivatives and other financial products. Implement risk analytics solutions on the Atoti platform, analyze pricing and valuation methodologies, investigate exposures and hedging strategies, and collaborate with clients, quants, risk managers, and engineering teams. Translate quantitative requirements into scalable technology solutions while supporting client workshops, product innovation, and risk management analytics across multiple asset classes.

11-week internship performing quantitative research to develop, backtest, and implement automated trading strategies. Translate mathematical models into code, analyze unconventional data sources, conduct statistical research (ML, time-series, NLP), and collaborate with senior researchers to refine trading signals and monetize models.

As a Quantitative Research Analyst Intern, you will model markets, develop algorithms, and conduct statistical analysis to enhance trading strategies.

Supports quantitative trading analysis by analyzing proprietary market data, developing execution signals and impact models, creating visualizations, backtesting trading features, and evaluating algorithm performance. The intern will work with quantitative analysts on execution strategies, market microstructure, statistical analysis, and client-facing research materials. This is a 12-week, New York-based internship requiring advanced Python, pandas, SQL, computational finance, statistics, mathematics, and exposure to machine learning.

As a Quantitative Research Analyst, you will develop and test automated trading strategies using statistical techniques and algorithms, conduct research, and analyze data.

Conduct research, statistical analyses, and develop automated trading strategies using large data sets and sophisticated statistical techniques.

Join the Indexes New Product Development team to design, develop, validate, and launch thematic and smart-beta indexes. Collaborate with research and product teams, build portfolio construction and analytics tools using statistical and machine learning methods, explore AI implementations, and produce white papers, factsheets, and client-facing materials to support product launches.

Conduct quantitative equity research supporting alpha generation, risk management, and portfolio construction. Build multifactor models using linear, nonlinear, and machine learning approaches; evaluate structured and alternative datasets; analyze risk exposures, optimization, performance attribution, and portfolio positioning; and provide recommendations to portfolio managers. Contribute to research projects, product development, fund pitches, client communications, and internal research publications.

Supports the design, implementation, testing, and improvement of valuation models for derivatives, structured products, swaps, fixed income, securitisations, and other complex financial instruments. Performs valuation analyses, Monte Carlo simulations, market data validation, output reviews, technical reporting, and client deliverables. The role also contributes to automation of valuation processes and applies quantitative methods from finance, mathematics, statistics, computer science, and economics.

Own the analytical and technical backbone of trading risk and fraud operations. Build production-grade infrastructure, monitoring tools, dashboards, and detection algorithms for toxic flow, latency arbitrage, and abusive trading. Investigate suspicious activity, assess product and promotion risks, classify clients for A-book/B-book decisions, and deliver solutions from data extraction through deployment. Improve automation, identify process gaps, report findings, and mentor junior analysts.

As a Quantitative Research Analyst, you will develop models, conduct complex data analysis, and work with stakeholders to optimize investment strategies.

Join a quant team to research and build predictive models for sports and trading. Apply advanced statistical and probabilistic methods, design models, collaborate with traders and developers, and contribute novel modeling techniques early in your career.

Front-office quantitative role supporting mortgage and ABS trading across European markets. Build and implement mortgage pricing, loan-level cashflow and recovery models, automate pricing/surveillance frameworks, and work closely with portfolio managers on complex non-agency and illiquid securitized assets.

Analyze large-scale post-trade data to review and refine client trading behaviour, implement performant C# production code, collaborate with research, engineering and front office, monitor real-world changes, and deliver medium-term strategic projects and urgent commercial improvements.

Serve as the bridge between research, product, and engineering to translate financial models into production; integrate advanced financial modeling into the platform; lead development of an automated data extraction and analysis tool; own product development lifecycle; collaborate across teams and produce clear, actionable analytical reports for stakeholders.