# Lead Data Scientist, Credit Risk

**Company**: Chime
**Location**: Chicago, IL
**Work arrangement**: hybrid
**Experience**: senior
**Job type**: full-time
**Salary**: $152,000-$210,000 USD
**Category**: Data Science
**Industry**: Finance

**Apply**: https://job-boards.greenhouse.io/chime/jobs/8788322002?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_74601f70-de8

## 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

## Skills

### Required
- Statistics
- Machine Learning
- Python
- SQL
- Microsoft Excel
- Looker
- Credit Risk Management
- Financial Services

### Nice to have
- subprime lending
- affiliate lending
- credit card line management
- alternative-data underwriting

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Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/chime/jobs/8788322002?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)