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.

Research, develop and implement asset-backed trading strategies and optimization models for large-scale batteries across multiple markets. Build backtesting and parameter-optimization pipelines, improve forecasting and ML models, support revenue simulations, and work with Trading & Portfolio Management to maximize asset performance.

Support Commercial Risk through daily/periodic risk reporting and VAR processes, develop and validate quantitative models for valuation and risk of complex gas and power transactions, perform price time-series analysis, ensure risk data quality, improve risk systems and reporting, and collaborate with traders and stakeholders to operationalise models and deliver ad-hoc analyses.

The Quantitative Research Analyst will research methods to improve trading systems, develop new trading signals, and optimize portfolio performance through quantitative analysis.

The role involves developing analytics infrastructure in Python, conducting quantitative research, analyzing trading strategies, and supporting portfolio management and business development initiatives.

Perform quantitative analysis using BMLL's product suite and large market-data lakes to support sales/marketing, prototype technical solutions, gather client feedback, and contribute to the product roadmap. Communicate results to technical and non-technical stakeholders, maintain reproducible documentation, and manage complex projects under tight deadlines.

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.

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.

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.

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.

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.

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.

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.

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.

Join PIMCO's Client Solutions & Analytics team in London to support asset allocation, risk management, ALM, and portfolio analytics. Develop and maintain quantitative models and tools, run risk analytics and scenario analysis, produce thought leadership, and use AI-enabled toolkits to streamline client deliverables while managing multiple projects.

Design and own pricing, demand forecast, forward curve and correlation models to value EV charging portfolios. Build and back-test optimisation and trading strategies, model imbalance and settlement risk, and produce scenario/stress analysis. Engineer models for automation and collaborate with backend/data teams to deploy production-quality analytical tools that inform trading and commercial decisions.

Develop, implement and calibrate derivatives pricing models for energy markets (gas, preferably power). Collaborate with trading, structuring, quant dev and quant risk to deliver C++ libraries and Python services for pricing, risk, backtesting and parameter estimation.