As a Data Scientist within the Credit Policy team of Square Financial Services (SFS), the role aims to provide crucial oversight and strategic direction for underwriting processes, monitor existing products and their performance for efficient underwriting, analyze and shape new product initiatives for growth, and ensure regulatory compliance through documentation and process.
Requirements
- Advanced proficiency with SQL and Python for data analysis
- Advanced proficiency building product metrics in data visualization tools (e.g. Mode, Looker)
- Working understanding of core ML concepts, with a focus on usage in decision making.
Responsibilities
- Analyze large datasets using SQL and Python to surface actionable insights that directly inform our product and credit strategy that drive business decisions
- Approach problems from first principles, using a variety of statistical and mathematical modeling techniques to research and understand customer behavior and loan performance
- Partner closely with ML engineers throughout the modeling lifecycle to develop, deploy, evaluate, and monitor models and credit policies
- Maintain and improve our systems for simulating the impacts of model/policy changes and the decision engine that implements those rules in production
- Develop KPIs and measurement systems focused on credit resiliency and product performance monitoring.
- Build, visualize and report on metrics that drive strategy and facilitate decision making for key business initiatives
- Effectively communicate your work with team leads and cross-functional stakeholders on a regular basis
Other
- Minimum of 8 years of related experience with a Bachelor's degree; or 6 years and a Master's degree; or a PhD with 3 years experience; or equivalent experience.
- A background in Statistics, Mathematics, Biostatistics, Economics or related quantitative field
- Direct experience in credit, lending, risk management, or financial services.
- Ability to turn unstructured business problems into concrete analyses that yield actionable insights and recommendations
- Work from anywhere: This role can be performed from any location in the US with the flexibility to work from home
