Quantitative Analyst (Fully Remote) in England

We are seeking a Quantitative Analyst to join our data-driven research team focused on leveraging alternative data and sentiment analysis for market insights. This role emphasizes in-depth quantitative research, model development, and rigorous backtesting of signals to drive actionable strategies. The ideal candidate will have a passion for financial markets and expertise in transforming raw data into clear, data-informed insights.

Key Responsibilities

• Conduct comprehensive quantitative analysis of hedge fund returns, risk metrics, and factor exposures to evaluate manager skill and strategy persistence.
• Develop and maintain proprietary analytical frameworks to decompose hedge fund performance, identify style drift, and assess risk-adjusted returns across market cycles.
• Perform detailed attribution analysis to validate managers' stated investment processes and verify alignment with reported results.
• Build and maintain risk factor models to evaluate strategy correlations, beta exposures, and potential portfolio overlaps across our manager universe.
• Analyze portfolio-level characteristics including liquidity profiles, position-level concentration, and counterparty exposures.
• Provide quantitative support to the CIO for manager evaluation and ongoing monitoring.
• Create detailed analytical reports for the investment committee, synthesizing complex quantitative findings into actionable insights.
• Acquire, clean, and normalize various alternative datasets (e.g., sentiment, social media, and ESG sources).
• Develop and refine predictive models and signals using time-series analysis, statistical modeling, and machine learning.
• Create robust backtesting frameworks to evaluate model performance and incorporate transaction cost or market impact.
• Build and monitor risk models, conduct stress testing under different market scenarios.
• Document and present research findings, methodologies, and performance metrics to stakeholders.

Required Qualifications

• Bachelor’s or Master’s degree in Finance, Economics, Mathematics, Computer Science, Engineering, or a related quantitative field.
• 1+ year of experience in quantitative research, data science, or analytics within financial services (buy-side or sell-side).
• Proven track record of building and validating quantitative models in real-world market environments.
• Proficiency in Python for data analysis (pandas, numpy, scipy) and modeling (statsmodels, scikit‑learn).
• Experience with databases (SQL or NoSQL) and large-scale data processing frameworks.
• Familiarity with statistical techniques (time-series analysis, regression, factor modeling, signal processing).
• Solid understanding of financial market structure, pricing, and liquidity.
• Knowledge of key asset classes (equities, fixed income, or derivatives).

Preferred Qualifications

• Advanced degree (Master’s/PhD) in a quantitative field (Financial Engineering, Statistics, or similar).
• Experience analyzing sentiment or alternative data (news feeds, social media, ESG, etc.).
• Background in machine learning, deep learning, or NLP for financial forecasting.
• Familiarity with cloud computing environments (AWS, GCP, or Azure) for large-scale data processing.
• Experience with portfolio optimization, risk analytics, or factor investing.