Data Scientist
ESSENTIAL FUNCTIONS:
To perform this job successfully, an individual must be able to perform each essential function at a high degree of proficient execution with little or no accommodation. The requirements listed below are representative, but not all inclusive, of the knowledge, skill, and/or ability required.
- Conceive, design & monitor risk management strategies to improve business profitability in the areas of underwriting, credit line management, universe expansion and alternative data evaluation for lending
- Participates in maintaining, developing, and implementing models includes design, development, validation, calibration, documentation, implementation, monitoring and reporting
- Provides expertise to build and improve quantitative and qualitative models for various models (including CECL, Prepayment, Weighted Average Remaining Maturity (WARM), Probability of Default and Loss Given Default (PD/LGD) methodologies)
- Compiles, analyzes, and resolves data errors/inconsistencies from various financial reporting systems
- Collaborates with business groups to develop effective modeling approaches to accurately represent the risks for practical business use
- Carries out regular model performance monitoring and produces comprehensive monitoring reports
- Supports analysis and reporting in stress testing models
- Develop credit policies for new lending products and iterate to improve underwriting criteria and loan amount/pricing strategies to maximize risk adjusted return and profitable revenue growth
- Determine underwriting criteria using new credit risk models in partnership with our data and finance team
- Set procedures to monitor risk and revenue of all credit products and performance across various lending partnerships
- Use machine learning and performance by variable to dynamically segment applicants and loans based on behavior and performance
- Recommend optimal segmentation strategy to build different models for different consumer segments
- Optimize underwriting criteria, risk-based pricing strategy, and collection strategy by leveraging data analytics
- Work with data team to track and analyze performance of various business and risk segments and programs to evaluate effectiveness
- Write LookML and SQL queries and build dashboards in Looker
- Supports ad hoc analytical projects, business analyses, and reporting
REQUIRED:
- Bachelor's degree (required) or advanced degree (preferred) in a quantitative field (mathematics, statistics, computer science, engineering)
- 2+ years of experience in Data Science, Credit Risk, Fraud Risk, Quantitative Analytics, Operations Analytics, Modeling or related field
- 2+ years of relevant experience within consumer credit risk management, ideally at a FinTech startup or lending company; bonus points for healthcare experience prefer
- 2+ years of experience in designing and authoring reports/dashboards using Looker (and similar tools like Tableau, Power BI) is required
- Preferred Experience in implementingDataPipelines leveraging Google Cloud products such as Cloud BigQuery, Cloud DataFlow, Cloud Pub/Sub, Cloud BigTable
- Understanding of data warehousing concepts, design, modeling, data engineering
- Work experience in Financial Services, preferably at a FinTech or consumer lending company, building risk strategies for several credit products (loans, lines of credit, credit cards). Experience in point-of-sale Healthcare a plus
- Familiarity with bureau data and alternate data is a strong preferred
- SQL experience, with programming experience in Python preferred
- knowledge on Cash flow modeling and loss forecasting is a plus
- Proven proficiency in basic statistics
- Skilled in analyzing, interpreting and summarizing data