An established investment manager is seeking a Quantitative Analyst to join its growing Portfolio Analytics & Data Science team. The role focuses on developing advanced quantitative tools and leveraging machine learning techniques to enhance portfolio construction and performance optimisation. The successful candidate will bring a strong combination of technical expertise and investment knowledge, particularly in public equities, fixed income, and private equity.
Responsibilities
- Develop and maintain quantitative tools and models for portfolio construction, capital allocation, and performance optimisation across multiple asset classes.
- Apply machine learning techniques, including Monte Carlo simulations and multifactor models, to generate actionable investment insights.
- Conduct systematic research aligned with investment strategies, focusing on both public and private markets.
- Build scalable and reusable analytics frameworks to enhance operational efficiency and support decision-making.
- Collaborate with portfolio managers, traders, and risk professionals to deliver impactful, data-driven solutions.
- Ensure rigorous documentation and governance of models and research outputs.
Requirements
- Master's or PhD in Mathematics, Statistics, Computer Science, Quantitative Finance, or a related discipline from a top-tier institution.
- At least 5 years of experience in quantitative research, portfolio analytics, or data science, ideally within an investment management or financial markets context.
- Proficiency in Python for data analysis and machine learning applications.
- Strong understanding of financial markets, including fixed income, public equities, and private equity.
- Experience with machine learning techniques such as clustering, time-series analysis, or predictive modelling.
- Ability to integrate financial knowledge with advanced data science methodologies.
- Excellent communication skills with the ability to collaborate across teams.
Preferred Experience
- Background in systematic trading strategies or quantitative research.
- Familiarity with private equity and alternative investment landscapes.
- Experience in developing tools for use by investment professionals.
