Quantitative Analysts - UK Wide
21 days ago
London
We work with a range of UK employers actively hiring across these roles. \n Job Description: \n UK-Based (On-Site, Hybrid or Remote) \n About the Role \n We're looking for talented Quantitative professionals at all levels—from Quantitative Analyst and Quantitative Researcher through to Quant Developer, Quantitative Risk Analyst and Senior / Lead Quant—for upcoming roles across the buy-side, sell-side, risk and fintech. This is where serious mathematics, programming and financial markets meet: you'll build the models that price instruments, manage risk and find the edge. \n You'll work across the full quantitative lifecycle—from research and model development through to implementation, validation and production. The role suits someone who pairs genuine mathematical and statistical depth with strong software engineering and the intellectual honesty to know exactly what a model can and can't be trusted to do. \n Key Responsibilities \n\n • Develop, test and implement quantitative models—pricing, risk, signal / alpha or execution\n, • Apply statistical and machine learning methods to financial and market data\n, • Build and maintain pricing and valuation models across one or more asset classes\n, • Develop risk models—VaR, stress testing, scenario analysis, market and credit risk\n, • (Buy-side) Research signals, develop strategies and run rigorous backtesting\n, • Productionise models in robust, well-tested code\n, • Work with large financial and market datasets and the pipelines behind them\n, • Validate models, document methodology and support model risk and governance\n, • Partner with traders, portfolio managers, risk teams and technology\n\n What You'll Bring \n Technical Expertise: \n\n • Strong programming skills—Python (NumPy, pandas, scikit-learn) and / or C++, R, q/kdb+, SQL\n, • Solid mathematics and statistics—probability, stochastic calculus, linear algebra, optimisation and time-series analysis\n, • Machine learning where it's applied to genuine financial problems\n, • Financial markets knowledge—instruments, pricing and risk across one or more of equities, FX, rates, credit, derivatives or crypto\n, • Discipline in modelling, backtesting and validation\n, • Big data and cloud tooling is a plus\n\n A note on background: this lane overlaps heavily with data science and ML engineering—if you're a strong Data Scientist or ML Engineer with the mathematical depth and an appetite to move into financial markets, we'd genuinely welcome the conversation. \n Analytical & Soft Skills: \n\n • Analytical rigour and intellectual honesty about model assumptions and limits\n, • Communication—able to explain a model to non-quant stakeholders\n, • A research mindset and real curiosity\n, • Strong attention to detail and a healthy risk awareness\n, • Collaborative approach across desks, risk and technology\n\n Domain Flexibility: \n\n • Roles span hedge funds and asset managers (buy-side), banks (sell-side), risk functions, trading firms and quant-driven fintech\n, • Background in any of these is welcomed; appetite to learn an adjacent asset class or desk valued just as much\n\n Experience Level: \n\n • Minimum 2+ years for Quantitative Analyst, 5+ for Senior, 8+ for Lead / Principal\n, • An MSc or PhD in a quantitative discipline (mathematics, physics, statistics, computer science, engineering or financial engineering) is common; CFA or CQF a plus\n, • Examples of models, strategies or risk frameworks you've developed and taken into production\n\n What We Offer \n\n • The opportunity to work where quantitative rigour translates directly into pricing, risk and returns\n, • Exposure to modern quantitative tooling, large financial datasets and production model environments\n, • Roles at the level you're ready for—we're hiring across the full quant spectrum\n, • A collaborative environment where mathematical depth and engineering craft are both valued\n, • A genuine bridge for strong data and ML talent looking to move into financial markets\n, • Flexible working arrangements (on-site, hybrid or remote) and supportive team culture\n\n Job Type: Full-time \n Benefits: \n\n • Flexitime\n, • Work from home\n\n