- Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed. Conduct analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
- Build and prototype analysis pipelines iteratively to provide insights at scale. Develop comprehensive knowledge of bank data structures and metrics, advocating for changes where needed for product development.
- Interact cross-functionally, making business recommendations (e.g., cost-benefit, forecasting, experiment analysis) with effective presentations of findings at multiple levels of stakeholders through visual displays of quantitative information.
- Research and develop analysis, forecasting, and optimization methods to improve the quality of bank's user facing products.
- Degree in a quantitative discipline (e.g., Statistics, Operations Research, Bioinformatics, Economics, Computational Biology, Computer Science, Mathematics, Physics, Electrical Engineering, Industrial Engineering) or equivalent practical experience.
- 2 years of work experience in data analysis related fields.
- Experience with statistical software (e.g.: Jupyter Notebook), programming languages (e.g., Python, R) and database languages (e.g., SQL).
- Master/PhD degree in a quantitative discipline.
- 4 years of relevant work experience, including expertise with statistical data analysis such as linear models, multivariate analysis, stochastic models, sampling methods.
- Applied experience with machine learning on large datasets.
- Experience articulating and translating business questions and using statistical techniques to arrive at an answer using available data.
- Demonstrated leadership and self-direction. Willingness to both teach others and learn new techniques.
- Demonstrated skills in selecting the right statistical tools given a data analysis problem. Effective written and verbal communication skills.
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