Description
We are looking for an experienced Credit Risk Data Scientist who is data-driven, has strong analytical and technical skills, and operates with a high degree of ownership.
In this role, you will lead the credit strategy that lets Chime lend to people before they have a relationship with us , starting with Instant Loans for new members and expanding to future unsecured credit products such as credit cards.
Responsibilities:
- Own credit strategy for new-to-Chime applicants across the member lifecycle, starting with Instant Loans for prospects and extending to future unsecured products such as credit cards and/or lines of credit
- Develop and evolve channel-specific credit policies that support growth while balancing risk, unit economics, and member experience
- Design and continuously iterate acquisition, loan amount / line assignment, pricing, line management, repayment, and collections strategies
- Leverage credit bureau data to underwrite applicants with no prior Chime relationship; build credit models and policies hands-on and in partnership with our DSML team
- Lead test-and-learn: design and read out champion/challenger tests and controlled ramps, and quantify trade-offs among approvals, losses, direct deposit conversion, and lifetime value
- Partner with Finance and Strategy to size new channels and forecast approval funnels, vintage losses, and unit economics; set launch criteria, guardrails, and expansion triggers
- Collaborate with data teams to build data infrastructure and early-read monitoring and dashboards
- Work with cross-functional teams including DSML, Product, Design, Engineering, and Decision Platform to test and implement risk models and strategies in production
- Partner with Compliance, Legal, Fair Lending, Model Risk Management, Fraud, and our bank partners to document, approve, and govern credit policies
- Mentor and work collaboratively with other credit risk data scientists to develop strategies, share knowledge, and raise the team's analytical bar
Requirements:
- A Master's degree in Statistics, Economics, Engineering, Math, Finance, Computer Science, or another quantitative discipline; a PhD is a plus
- 7+ years of analytical or data science experience in Financial Services, preferably at a FinTech company
- 4+ years of experience building and managing risk for unsecured credit products
- Hands-on experience with credit bureau data and prescreen, pre-approval, or direct mail credit programs
- Experience with credit furnishing, bankruptcies, delinquency, and write-off policies, and working knowledge of consumer lending regulation
- Excellent SQL and Python skills, advanced Microsoft Excel skills, and experience working in Looker or a similar business intelligence tool
- A strong grounding in statistics and machine learning for credit
- Hands-on, detail-oriented leader with exceptional communication skills
- Ability to work in a fast-paced, complex environment and meet ambitious deadlines while ensuring flawless completion
Nice to have: subprime or near-prime lending, affiliate or marketplace lending, credit card line management, or cash-flow / alternative-data underwriting experience
Benefits:
- Competitive salary ($152,000-$210,000 USD)
- Bonus(es) and competitive equity
- Comprehensive health, financial, and wellbeing benefits
- Generous vacation policy and company-wide paid days off
- 1% of your time off to support local community organizations of your choice
- Annual wellness stipend
- Up to 22 weeks of paid parental leave for birthing parents and 12 weeks of paid parental leave for non-birthing parents
- Access to family planning reimbursement