Quantitative Researcher

AAA Global; Greater London; On-site; GBP 70,000 - 100,000; Full time

Job summary

A major hedge fund in London is seeking a Systematic Equity Portfolio Construction Quantitative Researcher to develop and enhance portfolio construction and risk management frameworks. The ideal candidate will have 3-7 years in systematic equity research and strong Python skills. Responsibilities include translating machine-learning signals into robust portfolios and employing risk optimisation techniques. This position offers competitive compensation and opportunities for career progression in a dynamic, research-driven environment.

Benefits

Competitive compensation

Performance-based upside

Long-term career progression

Qualifications

• 3–7 years of experience in systematic equity research, portfolio construction, or quantitative risk.
• Strong academic background in quantitative disciplines.
• Advanced Python skills with libraries like NumPy and pandas.

Responsibilities

• Design and maintain portfolio construction and optimisation frameworks.
• Translate machine-learning alpha signals into investable portfolios.
• Implement risk-aware optimisation techniques.

Skills

Systematic equity research

Portfolio construction

Quantitative risk

Python

Machine learning

Education

Mathematics, Statistics, Computer Science, Engineering

Job description

Systematic Equity Portfolio Construction Quantitative Researcher

Location: London

Fund Type: Multi-Strategy Hedge Fund

Team: Systematic Equities / Central Quant

Role Overview

We are looking to hire a Systematic Equity Portfolio Construction Quantitative Researcher to join our systematic equities platform. The role focuses on designing and improving portfolio construction, optimisation, and risk management frameworks for alpha signals generated by machine learning and quantitative research teams.

You will work closely with systematic PMs and researchers to translate predictive signals into robust, scalable portfolios, optimising risk-adjusted returns while accounting for turnover, transaction costs, liquidity, and capacity constraints.

Key Responsibilities

• Design and maintain portfolio construction and optimisation frameworks for systematic equity strategies.
• Translate machine-learning-based alpha signals into investable portfolios with appropriate sizing and risk controls.
• Research and implement risk-aware optimisation techniques (mean-variance, risk parity, CVaR, drawdown-aware and robust optimisation).
• Build cross-sectional and time-series risk models, including factor exposure control and correlation management.
• Develop turnover, transaction cost, and liquidity-aware portfolio construction methods.
• Perform stress testing, scenario analysis, and regime-based risk analysis.
• Partner with PMs to refine signal weighting, portfolio constraints, and rebalancing logic.
• Productionise research in collaboration with engineering and trading teams.

Required Qualifications

• 3–7 years of experience in systematic equity research, portfolio construction, or quantitative risk within a hedge fund, asset manager, or proprietary trading firm.
• Strong academic background in Mathematics, Statistics, Computer Science, Engineering, or a related quantitative discipline.
• Advanced Python skills (NumPy, pandas, SciPy, optimisation libraries); Python is a must.
• Solid understanding of portfolio theory, optimisation, and equity market microstructure.
• Ability to communicate quantitative concepts clearly to PMs.

Preferred Experience

• Experience applying machine learning to portfolio construction, signal blending, or regime detection.
• Familiarity with transaction cost modelling (TCM) and capacity analysis.
• Exposure to multi-PM / pod-based platforms.
• Experience with large-scale data pipelines and research infrastructure.
• Knowledge of alternative risk measures and tail-risk modelling.

What We Offer

• Direct ownership of portfolio construction and risk frameworks for systematic equity strategies.
• Close collaboration with senior systematic PMs and researchers.
• Competitive compensation with strong performance-based upside.
• A highly technical, research-driven environment with real impact.Long-term career progression within a leading multi-strategy hedge fund.

Please email your CV to [e-mail] if you are interested in this role.