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Quantitative Researcher

Point72
CompanyPoint72
CategoryScience & Research
LocationTaiwan
RemoteOn-site (inferred)
EmploymentNot stated
LevelNot stated
SalaryNot stated by the employer
Posted11 Nov 2024
Last verified30 Jul 2026
SourceEmployer career page (greenhouse)
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Description
ABOUT POINT72 Point72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Point72 seeks to deliver superior returns for its investors through fundamental and systematic investing strategies across asset classes and geographies. We aim to attract and retain the industry’s brightest talent by cultivating an investor-led culture and committing to our people’s long-term growth. JOB RESPONSIBILITIES  The internal alpha capture (IAC) team is focused on developing and implementing scalable long/short equity investment strategies that leverage insights from discretionary portfolio managers and analysts, using sophisticated risk management, portfolio construction and execution techniques. This is an opportunity for students and researchers in quantitative finance, behavioral finance, and statistics to apply these techniques to solve niche practical investment challenges specific to a platform of equity portfolio managers. Specific responsibilities will include: End-to-end quantitative research project management including data exploration, cleaning and management, research hypothesis testing based on economic rationale, statistical/regression modeling, realistic simulation analysis, and presentation of results to the broader group. DESIRABLE CANDIDATES  Undergraduate, Masters, or PhD candidates or higher in finance, computer science, mathematics, or other quantitative discipline Strong analytical and quantitative skills, particularly related to quantitative equity investing Sound economic intuition when it comes to validating investment hypotheses Solid regression modeling foundations (linear, ridge, logit, etc.) Familiarity with fundamental data (estimates, actuals) and databases (compustat, ibes) Familiarity with commercial factor models (Barra, Axioma, etc.) Strong python skills, particularly in data manipulation and regression modeling Familiarity with SQL and version control (GIT) Commitment to the highest ethical standards
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