Quantitative Researcher

3 weeks ago


Boston, Massachusetts, United States Selby Jennings Full time

Responsibilities

Your responsibilities will evolve alongside your experience and capabilities. Depending on your strengths, typical responsibilities may include:

  • Consolidating, organizing, and analyzing extensive datasets from diverse origins.
  • Evaluating the quality of past and present data, identifying shortcomings, and proposing solutions.
  • Conducting ad-hoc exploratory statistical analyses across numerous complex datasets sourced from structured and unstructured channels.
  • Developing and maintaining production-level code directly contributing to the investment process.
  • Investigating discernible trends in asset returns, risks, trading expenses, and other data pertinent to financial markets.
  • Conducting research on portfolio construction utilizing our simulation tools.
  • Collaborating with software engineers to devise data feeds for new sources from third-party providers.
  • Contributing to data architecture decisions supporting the Research data platform.

Qualifications:

  • Currently enrolled in or graduated from an undergraduate or graduate program in finance, mathematics, economics, or a closely-related discipline with a focus on quantitative and financial analysis.
  • Demonstrated success in professional or academic pursuits (recent graduates are welcome).
  • Proficiency in analytical, quantitative, and problem-solving skills.
  • Familiarity with probability, statistics, linear regression, time-series analysis, linear algebra, calculus, optimization, and portfolio theory.
  • Understanding of statistical applications in economics (including econometrics or regression analysis).
  • Experience with statistical computing environments such as Python, Stata, R, or MATLAB.
  • Experience in analyzing large datasets.
  • Knowledge of finance, including equities and derivatives.
  • Passion for financial markets.
  • Strong communication skills, including proficiency in data visualization.
  • High energy and a strong work ethic.

Additionally, the following would be advantageous:

  • Solid understanding of empirical asset pricing in academic contexts.
  • Familiarity with financial data products.
  • Experience with stock market datasets.


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