Top Research Jobs in London

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

Build high-performance quantitative trading infrastructure, including market-data, backtesting, simulation, model-serving, execution, and monitoring systems. Develop low-latency C++ services and scalable Python research pipelines, optimize throughput and latency, productionize machine-learning models, and partner with researchers and traders to deploy reliable live trading strategies.

Lead research and development of Transformer-based and time-series foundation models for systematic trading. Responsibilities include pre-training models from scratch on large-scale financial datasets, designing representations and self-supervised objectives, developing distributed training systems, fine-tuning models for trading applications, studying scaling and regime robustness, and evaluating economic performance through simulations and live-trading metrics.

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 deploy statistical, machine learning, mathematical, and optimization models for Prime Finance. Responsibilities include forecasting borrow rates and demand, optimizing pricing and inventory allocation, researching alpha signals and hedging strategies, building analytics infrastructure, managing model risk, and communicating results to trading, technology, risk, and senior stakeholders. The role also mentors junior researchers and documents methodologies.

Develop and implement pricing models and risk-management strategies for base and precious metals. Maintain quantitative libraries and trading platforms, provide model-related analytical support, and enhance tools used by traders to hedge trades and aggregate positions. Collaborate with trading and sales teams to solve complex challenges, identify opportunities, and deliver thoroughly tested, documented solutions.

Develop and enhance high-performance portfolio construction and quantitative research technology. The role involves full software development lifecycle ownership, designing scalable systems, applying Python or Java expertise, collaborating with technologists and stakeholders, communicating development progress, and contributing to innovation and continuous improvement within a large financial-services engineering team.

Conduct quantitative research for systematic trading and financial markets. Develop mathematical models, algorithms, and infrastructure to price, hedge, and trade financial products. Perform alpha research, model calibration, portfolio optimization, and risk management while collaborating with traders, technologists, sales, marketing, and risk teams. Translate research into trading applications and communicate findings clearly. The program includes hands-on training and may lead to full-time employment.

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.

Partner with XVA trading and counterparty credit risk to design, develop, and deploy quantitative models and analytics for pricing and risk management. Translate business needs into solutions, provide production support, own implementation with Technology, and drive model governance and validation.

Conduct quantitative research for risk and treasury operations by analyzing data, backtesting strategies, developing and validating mathematical models, assessing model risks, and improving software tools. Collaborate with internal teams to optimize financial solutions across asset classes and instruments while presenting complex quantitative concepts clearly. The role is designed for PhD students and offers practical financial modeling experience with potential full-time opportunities.

Develop, test, and deploy software solutions for automated trading systems in partnership with Quantitative Researchers. Implement high-performance, scalable systems using advanced quantitative techniques, distributed computing, ML/NLP, and strong software engineering practices. Collaborate on priorities, deliver custom solutions, and engage with senior team members during an 11-week internship.

Lead private company coverage of fintech and payments firms: conduct fundamental research using traditional and alternative data, build models, write and market research notes, advise clients, build industry relationships, and coach junior analysts. Requires fintech/payments domain expertise and advanced data/market tool proficiency.

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.

Conduct applied AI research across the LLM lifecycle, including training, inference, agentic systems, evaluation, explainability, and reliability. Build and deploy practical AI systems from prototype to production, develop methods for detecting hallucinations and verifying workflows, and collaborate with researchers and business teams. The role includes documenting findings, presenting to technical and non-technical audiences, contributing to intellectual property, and publishing or presenting research at industry conferences.

Lead the strategic research direction for Wise’s Grow business area. Define research priorities, raise research quality and maturity, strengthen research practices, develop researchers, and use customer evidence to influence product strategy and senior decisions. The role combines people leadership with hands-on delivery of strategically important user research, while coordinating priorities across teams and guiding responsible use of AI and emerging tools.

Lead a Research Engineering team by owning roadmaps, delivery planning, hiring, resource allocation, performance management, and team culture. Partner with technical leads, Trading, and Quant teams to deliver applied research and trading products. Translate technical and business requirements into predictable delivery plans, manage dependencies and risks, develop engineers, and continuously improve team velocity and processes.

Lead ARIA’s executive assistant function while providing high-level support to the CEO. Manage the CEO’s diary, correspondence, meetings, travel, events, priorities, and follow-up actions. Coach and develop the EA team, establish efficient processes, coordinate board and committee administration, and build effective stakeholder relationships. Exercise discretion, anticipate needs, resolve competing demands, and ensure the Office of the CEO operates efficiently.

Conduct research and quantitative analysis across wholesale financial markets using large regulatory datasets, including transaction-level trading and derivatives data. Develop reproducible analytical code, identify market risks, evaluate regulatory outcomes, and produce evidence-based insights for policy and supervision teams. Collaborate with market experts and stakeholders, communicate complex findings clearly, and contribute to both ongoing research projects and time-sensitive market analysis.

Leads quantitative research for a crypto investment desk, overseeing strategy development, validation, deployment, risk management, portfolio construction, and research infrastructure. Establishes rigorous standards against overfitting and backtest bias, monitors live performance, manages exposure and drawdown limits, and evaluates liquidity and venue risks. Builds and mentors the quantitative research team, recruits researchers, allocates resources, and collaborates with trading, portfolio management, technology, and senior management.

Generate and close new business across defined territories, grow existing accounts, meet monthly sales targets, research markets and competitors, and support team development through coaching and mentoring. The role involves B2B sales, account management, negotiations, presentations, lead generation, and CRM usage.

Architect, engineer, and oversee delivery of complex corporate, colocation, and ultra-low-latency trading networks. Responsibilities include lifecycle management of switching, firewalls, load balancers, telemetry, CMDB, and automation platforms; designing software-driven network solutions; managing WAN traffic prioritization and steering; collaborating with project teams and vendors; and maintaining expertise in emerging networking technologies.

Develop speeches, briefing materials, and executive communications for the Group CEO and senior leaders. Identify speaking and thought-leadership opportunities, support executive engagement programs, shape corporate narrative and positioning, and collaborate with content, social, marketing, regulatory, and government-relations teams. The role requires strong writing, research, stakeholder influence, financial-market awareness, and the ability to manage complex priorities in a fast-paced environment.

Develop quantitative foundations for a risk and PnL management platform supporting trading across asset classes. Build risk models, scenarios, performance attribution, pricing integrations, and scalable analytics infrastructure. Collaborate with traders, quantitative researchers, pricing quants, and technology teams to translate requirements into production systems for real-time risk and performance management.