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Quantitative Researcher

Employer
Selby Jennings
Location
Boston, USA
Salary
Negotiable
Closing date
Feb 26, 2024

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Job Function
Other
Industry Sector
Finance - General
Employment Type
Full Time
Education
Bachelors
As a Quantitative Researcher, you will be engaged in impactful projects aimed at enhancing the specification and implementation of our investment models, as well as conducting research initiatives to improve decision-making in portfolio construction within our fully integrated, unified systematic investment process.

Responsibilities: Your responsibilities will evolve based on your experience and capabilities. Depending on your competitive advantages, you may be involved in the following typical tasks:
  • Merging, structuring, and analyzing substantial volumes of data from diverse sources.
  • Evaluating the quality of historical and current data, identifying deficiencies, and proposing corrective measures.
  • Conducting ad-hoc exploratory statistical analysis across multiple large and complex data sets from various structured and unstructured sources.
  • Developing and maintaining production-quality code directly utilized in the investment process.
  • Investigating predictable patterns in asset returns, risks, trading costs, and other data relevant to financial markets.
  • Conducting portfolio construction research using our simulation capability.
  • Collaborating with software engineers to design feeds for new data sources from third-party vendors.
  • Participating in data architecture decision-making to support the Research data platform.

Qualifications:
  • 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 professional or academic success, with recent graduates encouraged to apply.
  • Strong analytical, quantitative, and problem-solving skills.
  • Understanding of probability, statistics, linear regression, time-series analysis, linear algebra, calculus, optimization, and portfolio theory.
  • Knowledge of the application of statistics to economics, including econometrics or regression analysis.
  • Experience with a statistical computing environment such as Python, Stata, R, or MATLAB.
  • Experience analyzing large data sets.
  • Understanding of finance, including equities and derivatives.
  • Passion for financial markets.
  • Excellent communication skills, including proficiency in data visualization.
  • High energy and a strong work ethic.

Additional Considerations:
  • Good understanding of the academic field of empirical asset pricing.
  • Familiarity with financial data products.
  • Experience with stock market data.

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