Arrowstreet Capital
Quantitative Researcher
Boston
Sponsorship not specified$155k-$260kDetected 51 days ago
PythonMATLABData VisualizationStatisticsFinancial AnalysisRecruitingSTATAResearchCommunicationProblem Solving
About the role
- Your responsibilities are expected to grow in line with your experience and abilities.
- Arrowstreet Capital is committed to working with and providing reasonable accommodations for qualified individuals with disabilities and disabled veterans.
Responsibilities
- Working 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
- We maintain a friendly, team-oriented environment and place a high value on professionalism, attitude and initiative.
Requirements
- 1-3 years of relevant experience required
- 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
Nice to have
- Good understanding of the academic field of empirical asset pricing
- Familiarity with financial data products
- In addition, the following are a plus:
Compensation
- The base salary range for this position is $155,000 - $260,000 per year.
Benefits
- Experience with stock market data sets
- Degree from an undergraduate or graduate educational institution in finance, mathematics, economics, or a closely-related discipline emphasizing quantitative or financial analysis
Company info
- We are looking for Quantitative Researchers to join our Research group.
- We are a collaborative, data-driven, intellectually rigorous team responsible for coming up with investment ideas, codifying those ideas into signals, back-testing the signals, and producing return, risk and trading cost forecasts based on the signals to drive trading decisions.
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This listing is sourced directly from Arrowstreet Capital's careers page and normalized into a canonical job model.