Quantitative Researcher at Arrowstreet… · Boston

Summary: Arrowstreet Capital is a Boston-based systematic investment firm that manages global equity portfolios for institutional investors around the world. They are seeking Quantitative Researchers to join their Research group, where the role involves improving investment models and conducting portfolio construction research using complex data analysis. Responsibilities: - Performing ad-hoc exploratory statistical analysis across multiple large complex data sets from a variety of structured and unstructured sources - Researching predictable patterns in asset returns, risks, trading costs and other data relevant to financial markets - Writing and maintaining production-quality code used directly in the investment process - Assessing the quality of historical and current data, diagnosing deficiencies, and prescribing fixes - Performing portfolio construction research using our proprietary simulation capability - 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 Required Qualifications: - Degree from an undergraduate or graduate educational institution in finance, mathematics, economics, or a closely-related discipline emphasizing quantitative or financial analysis - 1-3 years of relevant experience required - Demonstrated professional or academic success - 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 data visualization - High energy and strong work ethic Preferred Qualifications: - Good understanding of the academic field of empirical asset pricing - Familiarity with financial data products - Experience with stock market data sets Required Skills: Quantitative analysis, Statistical computing, Data analysis Important Skills: Financial knowledge, Programming in Python Nice-to-Have Skills: communication, work ethic, Team collaboration Benefits: Annual discretionary bonuses, Robust benefits package