Financial Engineer - Portfolio Risk

Goldman Lloyds; Greater London; On-site; GBP 120,000 - 180,000; Full time

Job summary

Goldman Lloyds International seeks an experienced Financial Engineer to design and implement quantitative models for portfolio risk, factor exposures and investment decision making in a hedge fund setting.

You will collaborate with Risk Quants, Portfolio Managers and engineering teams to deliver scalable, production-ready analytics and data pipelines; 5+ years in related field required.

Job description

A leading hedge fund is seeking an experienced Financial Engineer to develop quantitative models and analytical frameworks supporting portfolio risk, factor exposures and investment decision-making. The position combines financial engineering, quantitative research and software development, working closely with Risk Quants, Portfolio Managers and Engineering teams to improve how portfolio risk is measured, attributed and understood.

Key Responsibilities

• Develop, calibrate and enhance equity multi-factor risk models, including the identification and measurement of systematic risk exposures.
• Build quantitative methodologies for factor decomposition, risk attribution, portfolio sensitivities and performance analysis.
• Research and implement statistical techniques supporting factor estimation, covariance modelling and portfolio risk measurement.
• Develop scalable analytical tools to evaluate portfolio exposures, concentration, diversification and risk-adjusted performance.
• Work with Risk Quants and investment professionals to translate financial modelling requirements into production-ready quantitative solutions.
• Engineer efficient data processing and calculation workflows capable of handling large volumes of market, security and portfolio data.
• Collaborate with software and data engineering teams on model implementation, analytical infrastructure and computational performance.

Requirements

• 5+ years of experience in Financial Engineering, Quantitative Risk, Quantitative Research or a closely related discipline.
• Essential: Strong practical experience developing, implementing or enhancing equity factor risk models, with a clear understanding of their mathematical foundations and applications.
• Strong understanding of factor exposures, covariance matrices, risk decomposition, portfolio construction and performance attribution.
• Experience modelling equities and equity-related financial instruments.
• Proficiency in Python for quantitative modelling, statistical research and analytical development; R, MATLAB or Julia experience also relevant.
• Strong SQL and data analysis skills, including working with substantial financial datasets.
• Familiarity with quantitative data pipelines, structured datasets and efficient analytical computation.
• Strong academic background in Mathematics, Statistics, Physics, Computer Science, Financial Engineering or a related quantitative field.
• Ability to collaborate with quantitative researchers, investment professionals and technology teams.
• Experience with Barra, Axioma or proprietary equity factor risk models.
• Knowledge of statistical factor estimation, regression techniques, covariance estimation and portfolio optimisation.
• Exposure to large-scale quantitative data platforms and distributed computation.
• Previous experience within a hedge fund, quantitative asset manager or investment bank.

The Opportunity

Work on sophisticated quantitative risk infrastructure within a global investment environment, with direct involvement in factor model development, portfolio analytics and investment risk methodology.