Top London Quantitative Analyst Jobs

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.

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.

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.

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.

Conduct quantitative and econometric analysis of sustainability, financial, economic, and climate data. Develop exploratory models, analyze geospatial datasets and climate impacts, support sustainable-investing products and analytics, research ad hoc business questions, and summarize findings for executives and clients. The role also involves project coordination, monitoring climate science and sustainable-finance trends, and collaborating across Morgan Stanley’s business divisions.

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.

Independent quant analyst producing systematic research and actionable trade ideas across equities, derivatives and multi-asset. Responsibilities include signal research, feature engineering, robust backtesting with realistic frictions, creating proprietary datasets and production pipelines, and communicating publishable, defensible insights to institutional clients while providing high-touch client service.

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.

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.

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, enhance and test Python-based financial models for fixed income and pension liabilities, portfolio optimisation, risk analytics and capital modelling; improve tooling, automate processes, support investment teams and resolve platform issues.

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.

Work directly with quantitative clients to translate event-driven datasets into tradeable strategies. Provide hands-on Python analysis, backtests, and reproducible examples; answer data quality and methodology questions; publish research and data notes; and liaise with product, research, and engineering teams to resolve client issues and inform priorities.