Overview

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.

Responsibilities:

Hedge funds:

• 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

Other asset classes:

• 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 Skills and Qualifications (MUST HAVES)

• 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 Skills and Qualifications (NICE TO HAVES)

• 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.

Next Steps:

Click "Apply" to start your application today!