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Quant Researcher - Factor Ressearch

Selby JenningsSan Francisco, CA🇺🇸United States

Quick overview

SeniorityMid Senior
Employment typeFull Time
Work modeHybrid
LocationSan Francisco, CA, United States
Equity ResearchForecastingPython

Job description

This opportunity is ideal for researchers who are intellectually curious about market behavior and passionate about understanding why investment factors generate returns, rather than simply identifying predictive relationships. Researchers are given significant ownership of the research agenda and work in a highly collaborative environment focused on developing durable, economically intuitive investment insights.

Responsibilities:

  • Develop and enhance proprietary equity factors and systematic investment signals.
  • Study the drivers of stock returns and market anomalies through empirical research.
  • Evaluate the economic rationale, persistence, and robustness of investment factors across market regimes.
  • Perform factor attribution, return decomposition, and exposure analysis to explain portfolio performance.
  • Research fundamental, behavioral, and alternative-data signals that may improve stock selection models.
  • Build and maintain scalable research tools, datasets, and analytics supporting the factor research process.
  • Communicate research findings and contribute to the team's ongoing research agenda.

Preferred Qualifications:

  • Advanced degree in Finance, Economics, Statistics, Mathematics, Physics, Computer Science, Engineering, or a related quantitative field.
  • 3+ years of experience in quantitative equity research, factor investing, systematic equities, or related investment research roles.
  • Strong understanding of factor models, equity return forecasting, risk attribution, performance attribution, and systematic investing.
  • Experience researching equity factors such as Value, Momentum, Quality, Growth, Profitability, Revision, Sentiment, or Crowding.
  • Strong Python programming skills and experience working with large financial datasets.
  • Ability to clearly communicate quantitative research to both technical and investment audiences.

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