Top London Quantitative Analyst Jobs

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.

Front-office quant team role designing, implementing, testing and deploying high-performance valuation models and pricers for derivatives. Collaborate with trading desks, engineering, and risk to digitalize derivatives business, optimize performance, deploy models across platforms, support daily trading floor activities, and drive technical innovation.

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

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

Develop and manage counterparty credit risk analytics and models for fixed income products, including repos, securities lending, mortgages, and interest rate derivatives. Responsibilities span model design, implementation, validation, monitoring, back testing, quantitative research, dashboard development, risk analysis, and model governance. The role partners with business, risk, technology, and other stakeholders to enhance model infrastructure and support daily risk management.

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.

Validates financial risk and pricing models, develops challenger models, monitors model performance, and maintains the risk model library. The role also manages model risk governance, prepares technical validation reports and senior management briefings, and supports the organization’s model risk management framework. Strong quantitative analysis, Python and SQL programming, Power BI experience, and knowledge of regulatory requirements for model risk or clearing are required.

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

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 investment research for institutional investors, developing systematic strategies, factor and alpha models, event-driven frameworks, and cross-asset analyses. Build proprietary datasets, signals, models, and production pipelines using rigorous backtesting, validation, and realistic transaction-cost assumptions. Publish concise, differentiated investment insights, defend research in client discussions, and provide high-touch service to select institutional clients.

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.

Develop, test, document, monitor, and maintain behavioral and interest rate risk models for Treasury’s IRRBB and ALM functions. Analyze customer behavior and bank products, expand Python quantitative tools, support hedging strategies, and provide quantitative modeling expertise across Treasury. The role requires strong Python and SQL skills, statistical modeling, applied machine learning, data manipulation, and the ability to communicate complex analysis clearly.

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.

Validate, challenge and enhance firmwide risk and quantitative models across asset classes; produce validation reports; present findings to governance committees; support model development and ML model monitoring; design automation and tools to improve risk processes and monitor business-critical tool performance.

Build and maintain pricing, risk, portfolio construction and analytic tools for derivatives and derivative strategies. Model risks across fixed income and other assets, support portfolio managers with analysis, participate in IT and process projects, and ensure instruments are priced and reported in line with market conventions.

Develops quantitative equity models, alpha signals, factor research, valuation frameworks, and investment insights across global markets. Conducts macroeconomic and equity research, publishes client-facing reports, presents findings to institutional investors, and supports the equity quantitative research platform. The role also requires regulatory compliance, maintaining applicable licenses, and potentially mentoring junior researchers.

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.

Develop and implement quantitative algorithms and statistical models to produce and publish forward pricing curves for illiquid commodity markets using Matlab, SQL and Excel; monitor curve performance daily, respond to client requests, update documentation, and collaborate with sales, product and editorial teams.

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.

The Quantitative Analyst will analyze trading behavior, collaborate with teams, and improve trading strategies using data and skills in Python and C#. Attention to detail and prioritization are essential for success.