Jobs in London - Quantitative Researcher • Central London

Company: Selby Jennings London

Central London

Job Title: Portfolio Optimisation Quant Location: London Employment Type: Full-Time About the Role We are seeking a highly skilled Portfolio Optimisation Quant to join our investment team. The successful candidate will play a key role in designing, implementing, and maintaining portfolio construction and optimisation frameworks that enhance risk-adjusted returns across multiple strategies. This is an opportunity to work in a dynamic, fast-paced environment where quantitative innovation drives investment decisions. Key Responsibilities Develop and maintain portfolio optimisation models using advanced quantitative techniques (e.g., mean-variance optimisation, risk parity, factor-based approaches). Implement risk management frameworks, including stress testing, scenario analysis, and liquidity constraints. Collaborate with portfolio managers and researchers to integrate optimisation tools into the investment process. Analyse large datasets to identify patterns, correlations, and actionable insights for portfolio construction. Enhance existing optimisation algorithms to incorporate transaction costs, turnover constraints, and regulatory requirements. Build and maintain production-level code for optimisation systems in Python/C++ or similar languages. Monitor and improve performance attribution and risk decomposition across portfolios. Stay up-to-date with academic research and industry best practices in portfolio theory and quantitative finance. Required Skills & Qualifications Advanced degree (Master's or PhD) in Quantitative Finance, Mathematics, Statistics, Computer Science, or related field. Strong understanding of portfolio theory, optimisation techniques, and risk management principles. Proficiency in Python, C++, or similar programming languages; experience with numerical libraries (e.g., NumPy, Pandas, SciPy). Solid knowledge of linear algebra, convex optimisation, and stochastic processes. Experience with data analysis, machine learning, or factor modelling is a plus. Familiarity with market microstructure, transaction cost modelling, and liquidity constraints. Excellent communication skills and ability to work collaboratively with investment professionals. Preferred Experience Previous experience in a hedge fund, asset management firm, or proprietary trading environment. Exposure to multi-asset portfolios, including equities, fixed income, derivatives, and alternative investments. Knowledge of cloud computing and distributed systems for large-scale optimisation.