Own and monitor a consumer lending portfolio; develop and implement underwriting, limit, pre-screen, and risk-tier strategies. Perform hands-on analysis with SQL and Python, run A/B and champion/challenger tests, use internal and third-party data, ensure fair lending governance, and collaborate across stakeholders to translate analysis into business recommendations.
Work Location: San Francisco or Dallas/Frisco or New York
Work Mode: 1-2 days/week in office
Pay Range: $140K/Yr - $160K/Yr Base + Annual Bonus
The posted range is the hiring range for this role — a subset of the broader range available to employees over time — and reflects base salary across our national hiring scale. Final offers are based on several factors, including the candidate's skills and experience, internal pay equity, work location, market conditions for the role, and the specific scope and responsibilities of the position. The top of the range is reserved for candidates who notably exceed the requirements; the lower end applies to those with less experience or fewer preferred qualifications. For positions based in higher-cost zones (e.g., California, New York, New Jersey), actual compensation may exceed the posted range; your recruiter will share specifics during the process
For more information on benefits and what we offer please visit us at US Careers and Benefits
- Own a portfolio. Own an assigned consumer lending portfolio (personal loans, credit card, student loan refinance) — monitor risk and performance and recommend strategy enhancements.
- Build strategies. Develop and implement underwriting, line/loan-amount, pre-screen, and risk-tier strategies aligned to the client’s risk appetite.
- Analyze hands-on. Use SQL and Python to analyze large datasets and identify drivers of losses, approvals, and profitability.
- Test and optimize. Run champion/challenger and A/B tests to improve approval, pricing, and limit strategies — balancing risk, revenue, and customer experience.
- Leverage data. Use internal, bureau, third-party, and alternative/cash-flow data to strengthen decisioning.
- Govern fairly. Conduct fair lending testing and ensure alignment with client policies and regulatory requirements.
- Partner broadly. Collaborate across Business, Operations, Marketing, Finance, Product, Engineering, Legal, and Compliance to deploy strategies accurately.
- Communicate clearly. Translate analyses into crisp insights and presentations for client stakeholders and leadership.
- Own a portfolio. Own an assigned consumer lending portfolio (personal loans, credit card, student loan refinance) — monitor risk and performance and recommend strategy enhancements.
- Build strategies. Develop and implement underwriting, line/loan-amount, pre-screen, and risk-tier strategies aligned to the client’s risk appetite.
- Analyze hands-on. Use SQL and Python to analyze large datasets and identify drivers of losses, approvals, and profitability.
- Test and optimize. Run champion/challenger and A/B tests to improve approval, pricing, and limit strategies — balancing risk, revenue, and customer experience.
- Leverage data. Use internal, bureau, third-party, and alternative/cash-flow data to strengthen decisioning.
- Govern fairly. Conduct fair lending testing and ensure alignment with client policies and regulatory requirements.
- Partner broadly. Collaborate across Business, Operations, Marketing, Finance, Product, Engineering, Legal, and Compliance to deploy strategies accurately.
- Communicate clearly. Translate analyses into crisp insights and presentations for client stakeholders and leadership.
- Bachelor’s in a quantitative discipline (Statistics, Mathematics, Economics, Computer Science, Data Science, Engineering, or related); Master’s preferred.
- 5+ years in credit risk, credit strategy, or risk analytics — ideally in consumer lending (banking, fintech, or analytics consulting).
- Strong hands-on SQL and Python skills for data extraction, manipulation, and analysis.
- Working knowledge of decision trees / segmentation and credit lifecycle concepts (underwriting, roll rates, vintage analysis).
- Demonstrated experience owning or developing credit strategies and monitoring portfolio performance.
- Strong problem-solving skills and the ability to turn data into actionable, business-facing recommendations.
Excellent communication and stakeholder-management skills — comfortable operating as an embedded consultant.
Preferred
- Personal loan or credit card credit risk experience.
- Experience with alternative/cash-flow data, scorecard development, or decision engines.
- Exposure to visualization tools (Tableau / Power BI) and version control (Git).
- Prior client-facing or consulting experience.
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