Quantitative Analyst, Portfolio Research

New York, New York, United States

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Responsible for using knowledge of and experience with finance/economics, probability, statistics, algorithm, and linear algebra to research, analyze, develop and implement scientific solutions in portfolio and investment management using advanced quantitative statistical models  and effectively implementing the results to computer based quantitative solutions for institutional investors on portfolios with global exposure; generate hypothesis and designing research to analyze and fit Two Sigma’s market impact and transaction cost and construct mathematical/statistical models for prediction and evaluation; generate ideas and conduct analysis to support all aspects of the portfolio management and risk optimization process, from providing research on risk estimation, to portfolio hyper-parameter optimization; Actively analyzing portfolio performance, running simulations, and pursuing a wide-range of research to improve fund performance; Developing tools to enhance the portfolio management process through better evaluation metrics and automation.

Requires a Master’s degree or equivalent in Finance, Statistics, Mathematics, Engineering, or related field, plus 4 years of experience in statistical modeling or related experience.

Must have experience with the following:

  • Conducting research projects.
  • Scientific computing, algorithm development, and data science.
  • Demonstrated knowledge of risk concepts essential to portfolio management as evidenced by certification/licensure of at least one industry standard credential (CFA, FRM, CAIA or FINRA Series).
  • Demonstrated knowledge of macroeconomic concepts and an array of financial asset classes and instruments.
  • Demonstrated knowledge of linear algebra, time-series analysis, statistical estimation, Monte Carlo methods, Bayesian techniques and factor analysis.
  • Demonstrated coding skills in either Python, Java, or Groovy.
  • Demonstrated knowledge of Unix operating environment, Pandas or equivalent time series analysis language, and SQL.

Must also pass company’s required skills assessment. 

Employer will accept any amount of professional experience with the required skills.

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