Top Research Jobs in London

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.

Supports Wise’s Design & Research Operations team through community operations, cross-functional program delivery, design feature rollouts, capability building, process improvement, training, and feedback gathering. The graduate will collaborate with design, research, product, and leadership teams while developing project and operational management skills.

Conduct research on AI compute, machine learning algorithms, large language models, efficient inference, numerics, world models, molecule generation, or model safety. Implement models and algorithms in Python or C++, design and analyze experiments using frameworks such as PyTorch, and communicate findings through technical presentations or research papers under experienced mentorship.

Designs and maintains production-grade algorithmic trading systems and execution platforms for systematic Rates markets. Translates quantitative research into scalable strategies, collaborates with traders and researchers on models, hedging, risk, and allocation, and optimizes latency and throughput. The role also emphasizes automated deployments, observability, production support, documentation, and continuous improvement of live trading infrastructure.

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

Develop and implement pricing, risk, and quantitative trading models for EMEA rates exotics. Partner with trading, technology, and model risk teams to translate product ideas into production-ready solutions, automate workflows, analyze market data, document models, and support governance approval. The role also sets technical direction, coordinates business priorities, maintains strong risk controls, and mentors junior quantitative professionals.

Conduct commercially oriented AI/ML research across areas such as synthetic data, foundation models, reinforcement learning, multimodal AI, multi-agent systems, formal reasoning, and privacy-preserving machine learning. Formulate research problems, develop algorithms and models, run experiments, evaluate results, write high-quality Python code, communicate findings, and contribute to production-scale financial services applications.

Provides compliance advisory support to EMEA and global research teams, focusing on research independence, conflicts of interest, information barriers, regulatory obligations, and reputational risk. Develops policies, training, risk assessments, monitoring activities, and control processes. Investigates and escalates compliance issues, supports audits and regulatory examinations, and manages cross-functional compliance projects across regions and business lines.

Conduct foundational research on latent space models for voice AI, including neural audio codecs, generative speech, interpretable embeddings, synthetic data generation, multimodal speech-to-speech systems, and hardware-efficient model architectures. Design mathematical formulations, scalable data pipelines, controlled experiments, and real-time inference solutions for large-scale audio datasets.

Designs and deploys AI, LLM, generative AI, and machine learning solutions for credit trading workflows. Responsibilities include generating trading signals, optimizing portfolios, identifying credit exposures and hedging strategies, automating risk and position reporting, and developing trade-support infrastructure. The role collaborates with model control teams and global quantitative research groups to support compliance, portfolio management, and digital transformation.

Leads quantitative research for rates trading, developing pricing and risk models, implementing production-ready analytics in Python or C++, and translating market opportunities into scalable solutions. Partners with trading, technology, and model risk teams to support model governance, automation, and disciplined controls. Manages and mentors a local team while coordinating priorities for the EMEA business.

Conduct quantitative research and develop analytics, models, and end-to-end tools for credit electronic trading, including corporate bonds, bond portfolios, and CDS indices. Collaborate with market makers and risk managers to improve systematic market-making strategies. Apply statistical, financial mathematics, and AI/ML techniques, including deep learning and time-series modeling, to build scalable production solutions and translate market data into actionable trading insights.

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.

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.

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.

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.

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.

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.

Own top-of-funnel go-to-market activities for Watcher, including account and prospect research, personalized outbound, conference strategy, CRM hygiene, pipeline reporting, and workflow automation. Test segments, messaging, and channels, develop repeatable account engagement processes, and collaborate closely with the GTM lead and product team. The role may develop toward account executive, GTM operations, or partnerships responsibilities.

Own the full enterprise sales cycle for Watcher, from account mapping and targeted outbound through discovery, demos, technical evaluations, POCs, security reviews, procurement, negotiation, and close. Build the sales and CRM playbook, develop enterprise ROI cases, accelerate evaluation cycles, provide product and market feedback, and help shape future hiring. The role targets security and engineering leaders at large organizations and requires technical credibility, startup experience, and high ownership.