What You'll Do
Design and implement predictive models to improve lending decisions using statistical techniques and simulation methods. Analyze large-scale data to uncover patterns in consumer risk behavior and assess how these impact portfolio performance and business strategy.
Collaborate with software engineers to integrate models into production systems and conduct post-deployment evaluations to ensure accuracy and effectiveness. Help build internal tools and platforms that standardize modeling workflows and monitoring practices across teams.
Define key performance indicators and create automated dashboards using SQL and Python to track model performance and business outcomes. Lead A/B testing initiatives for underwriting strategies, interpret results, and advise on data-driven improvements. Partner with cross-functional stakeholders to identify new analytical opportunities and deliver clear, strategic recommendations to leadership.
Requirements
- Bachelor’s degree in a quantitative field or related discipline
- Minimum of two years of professional experience in data analytics or statistical modeling
- Proficiency with SQL and relational databases
- Programming experience in Python for data analysis and modeling
- Strong analytical and problem-solving abilities with a focus on precision
- Proven ability to collaborate effectively in fast-paced, cross-functional environments
Preferred Qualifications
- Advanced degree in mathematics, statistics, engineering, quantitative finance, or a similar field
- Background in specialty finance, FinTech, or consumer lending
- Experience in marketing analytics or customer segmentation
Technical Stack
SQL, Python
Benefits
- Competitive salary and comprehensive benefits
- Flexible remote work options with support for global locations
- Opportunity to make a meaningful impact in a growing company
- Innovative, lean culture focused on transforming consumer finance
- Convenient office location in downtown Chicago
