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Strong global brand, popular mid-level data role, metro location, and broad skill requirements increase competition.
Finance-specific quant, portfolio construction, and factor research requirements limit cross-industry transferability.
Mandatory 2+ years plus required Python, SQL, and quantitative libraries creates strict shortlisting filters.
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Conduct asset allocation, manager evaluation research, and bespoke client portfolio analysis for internal and external clients.
Build and maintain databases, perform data collation, cleansing, and analysis using SQL and Python; develop data visualization dashboards (Python Dash).
Apply statistical modeling and machine learning techniques to quantitative problems; deliver research projects with quantitative applications to fundamental strategies using AI tools.
At least 2 years of experience in RDBMS database design, preferably with MS SQL Server.
At least 2 years of Python development experience with proficiency in libraries such as pandas, numpy, and statsmodels.
Strong capability to manipulate large datasets with high attention to detail and accuracy.
Educational background in Mathematics, Physics, Statistics, Econometrics, Engineering or related field.
Experienced in building quantitative models, including factor research, portfolio construction, and systematic models.
Comfortable working on quantitative asset management problems and delivering research for global clients.
Skilled in leveraging AI tools for data handling, research, and modeling processes.