Hi, we're Brigit! A holistic financial health company helping everyday Americans build a brighter financial future. With a business model that is aligned with our customers, we create transparent, fair, and simple financial products that put money back in the hands of our members, help them spend wisely, avoid unfair fees and build their credit quickly. If autonomy, ownership, and having meaningful input at the company you work for is important to you, come join our growing team!

Brigit is doing innovative and exciting work, but don’t just take our word for it, our work is being recognized by others:

Built In's 2026 Best Midsize Companies to Work For in New York City

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Built In’s 2024 & 2025 Best Startups to Work For In the U.S.

Built In’s 2023 - 2025 Best Startups to Work For In New York City

Fast Company’s Most Innovative Companies of 2022

Business Insider’s Most Promising Consumer Startups 2022

Forbes Fintech 50 2022

Role overview

In 2026, Brigit launched Instant Cash as an embedded product for Experian's consumers. This partnership went from a small pilot to open availability in six months, and is now one of the largest sources of new cash advance volume at Brigit.

This is a Senior role on the Data Analytics team at Brigit, embedded in our Instant Cash Partnerships pod alongside Product and Engineering. Day-to-day, you’ll analyze repayment performance of the Experian portfolio, evaluate underwriting and credit limit changes, model cohort LTV and unit economics, and dig into the funnel from account creation through first advance. You’ll also own the Experian analytics layer itself: the dbt models, data definitions and reporting, and data quality monitoring that the pod, Finance, and our partners at Experian rely on.

The ideal candidate has done risk or portfolio analytics on a consumer credit or earned wage access product, and is comfortable being the sole analyst in the room with Product, Engineering, and Partnerships.

What you’ll be doing

Credit Risk and Portfolio Performance

Own delinquency and non-payback reporting for the Experian portfolio: vintage curves, delinquency roll rates, gross and net loss, and recoveries

Evaluate underwriting model and credit limit strategy changes end to end: size the population, model the approval / loss tradeoff before launch, and read out actual vs. modeled performance after

Analyze the collections lifecycle (scheduled repayments, retry flows, charge-offs, etc) and recommend changes that improve repayment rates without degrading member experience

Build and refine alerting to detect anomalies quickly, respond to incidents, and identify emerging risk trends

Maintain and extend our partner-level LTV model, tracked to maturity by monthly cohort

Stakeholder Partnership

Be the analytical partner to the Experian Product Manager and Tech Lead: shape the roadmap with data, pressure-test proposals, and make sure decisions are measured after they ship

Work with the Partnerships team on what data is shared bi-directionally between Brigit and its partners and how, including preparation for quarterly business reviews

Partner with Finance on portfolio tracking, revenue coverage, and the projections that inform partnership commitments and quarterly business reviews with Experian

What you have

4–6 years of experience in risk analytics, portfolio analytics, or product analytics at a consumer credit, earned wage access, or fintech lending company

Advanced SQL — you write complex queries from scratch, and you've built or maintained data models in dbt or a comparable framework

Experience with product funnel analysis, A/B testing, and experiment readouts

Sharp investigative instincts — you can take a vague report ("something looks off in collections"), form hypotheses, find the root cause, and size the impact

Strong written and verbal communication

Comfortable being the single analyst embedded in a cross-functional pod, where ownership is expected and priorities shift

Nice to Have

Fluency in consumer credit performance concepts: vintage analysis, roll rates, gross vs. net loss, unit economics, and how underwriting and credit limit decisions move each of them