Quantitative Analyst; Fully Remote

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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.

• 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 counter party 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

• 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 (stats models, scikit‑learn).
• Experience with databases (SQL or No
  
  SQL) 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).

• 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.

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