Credit Risk Analyst (Portfolio & Underwriting)

Atlas•San Francisco, CA

12h

About The Position

Atlas is hiring a Credit Risk Analyst to own the view of portfolio performance and help shape credit policy and underwriting analytics. The role focuses on measuring delinquency, losses, exposure, and policy performance so Atlas’s founders and credit engineering team can understand portfolio health and make informed decisions. It is a newly created position with latitude to define how credit performance is measured, working directly with the engineers building underwriting models. Atlas’s mission is “Credit Made Easy,” expanding access to credit for applicants without an existing credit history. Its products include the Atlas Rewards Mastercard, a deposit account, credit score tracking, a subscription manager, a tax filing service, and cash back at more than 50,000 locations. The company describes itself as a small, high-trust, high-ownership team that practices radical transparency and rewards impact. The compensation range is $120,000–$180,000, with competitive salary and market-leading equity.

Requirements

At least 3 years of experience in credit risk, credit strategy, underwriting analytics, or a closely related analytical role.
Strong credit intuition or a clear ability to develop it quickly.
Strong SQL and Python skills and the ability to work independently in Atlas’s BigQuery warehouse.
Active use of AI tools for writing queries, exploring data, and accelerating analysis, or eagerness to learn quickly, together with judgment about verifying AI output.
Comfort with ambiguity and with working on problems that are not fully defined.
Ability to learn quickly and take ownership of shaping a new role.
Clear communication skills, including making precise requests to engineers and concise recommendations to founders.

Nice To Haves

Experience at a card issuer, lender, or lending fintech.
Experience with cash-flow or bank transaction data, such as Plaid or other open banking sources.
Familiarity with evaluating machine-learning underwriting models, including calibration, segment performance, and SHAP or other attribution methods.
Exposure to transformer- or embedding-based risk models.
Background in model validation or model risk management.
Experience in an adjacent analytical field such as quantitative finance, fraud, insurance, or economics, with an ability to learn credit quickly.

Responsibilities

Build and maintain portfolio performance reporting, including delinquency and loss curves, vintages, roll rates, and performance by segment; identify emerging issues and explain their drivers.
Track credit limit history, line increases, and growth in unsecured exposure; evaluate whether the limit strategy is appropriately balancing growth and risk and recommend where to expand or pull back.
Evaluate credit cutoffs, eligibility rules, and limit assignments; estimate the approval, loss, and exposure impacts of proposed policy changes and measure their actual outcomes.
Define bad definitions, performance windows, and evaluation sets used to assess policy and model decisions.
Partner with credit engineering to analyze model performance by segment, identify prediction gaps, and translate findings into specific requests for features, data sources, or signals.
Help design tests to determine whether changes are effective.
Monitor production models and policies for calibration, drift, and stability, and build recurring credit reporting.
Contribute to fair lending testing, adverse action reason quality, and credit documentation.