A fast-growing fintech leader in the consumer credit space is seeking a Credit Risk Manager – Acquisition Strategy to join their high-impact team. This is a unique opportunity to shape the future of credit risk strategy at a company focused on expanding responsible credit access to underserved consumers using advanced analytics and machine learning.
In this role, you’ll lead the development and optimization of acquisition strategies, balancing risk and growth through data-driven credit decisioning. You’ll work cross-functionally with product, data science, and compliance teams to deliver scalable solutions that drive profitable customer acquisition and portfolio performance.
Key Responsibilities
Acquisition Strategy & Credit Risk Management
- Develop and refine credit risk policies for new customer acquisitions across loan and credit products.
- Design and implement underwriting strategies that align with business goals and risk appetite.
- Utilize advanced analytics and machine learning to enhance credit decisioning models.
- Collaborate on risk-based pricing, credit limit assignment, and segmentation strategies.
- Monitor performance trends and economic indicators to adjust acquisition tactics in real time.
- Incorporate alternative data sources (e.g., behavioral data, cash flow) to improve underwriting efficiency.
- Partner with data scientists to develop and validate credit risk models.
- Conduct A/B testing to assess and optimize acquisition performance.
- Track KPIs such as approval rates, early delinquency, and customer lifetime value.
- Ensure underwriting practices align with applicable regulatory standards (e.g., CFPB, OCC).
- Collaborate with legal and compliance teams to uphold fair lending and consumer protection practices.
- Stay informed on regulatory developments impacting subprime and non-prime lending.
- 5+ years’ experience in credit risk, acquisition strategy, or consumer lending analytics.
- Strong knowledge of credit bureau data, alternative data, and risk model development.
- Experience with subprime or near-prime lending preferred.
- Proficiency in SQL and one or more of: Python, R, or SAS.
- Exposure to machine learning in a credit risk context is a strong plus.
- Bachelor’s degree in a quantitative or financial discipline (Master’s preferred).
- Exceptional analytical, communication, and problem-solving skills.
- Salary up to $190,000, plus performance-based bonus
- Comprehensive benefits package
- Remote-first flexibility with optional hybrid work
- Work alongside a highly skilled, collaborative team of data scientists and risk experts
- Career growth in a mission-driven, innovation-focused fintech
If you’re passionate about data-driven decision-making, fintech innovation, and empowering underserved consumers, we’d love to hear from you.
