A top consumer lending fintech in the Dallas area is in high growth mode and looking to expand their credit risk division. This role would require an individual with a highly quantitative background who has experience using SAS, SQL, and other query tools in the subprime lending sector. The ideal candidate can work with large databases, build models, and facilitate extensive inquiries.
- Build complex predictive models that support the credit risk teams
- Collect and analyze big sets of data and make recommendations to manage customer risk
- Lead data mining and collection procedures
- Develop predictive models, underwriting strategies, and pricing parameters and ensure data quality and integrity
- Monitor risk models, decision engine logic, and pricing parameters
- Bachelor's degree required (Master's degree preferred) in quantitative background such as statistics, engineering, etc
- Proficient use of query tools (SQL, SAS, R)
- 6+ years of experience
- Decision analytics, risk modeling and/or predictive statistics background
- Experience with data architecture, data mining and data integration
- Experience in Financial Services and Subprime Lending preferred.
- Health care