Data Analyst, Lending

Chime
San Francisco, CAUp to $150kPosted 24 February 2026

Job Description

<h3><strong>About the Role</strong></h3> <p>As a Data Analyst supporting Chime’s lending portfolio, you will help drive data-informed decisions that improve member liquidity and lending experiences. You’ll work closely with Product, Risk, Finance, Marketing, and Analytics partners to analyze performance, support experimentation, and surface insights across the lending funnel. This role is well-suited for an analyst who is building strong fundamentals in product and financial analytics and is eager to grow their impact in a fast-paced environment.</p> <p>The base salary offered for this role and level of experience will begin at $109,000 and up to $150,000. Full-time employees are also eligible for a bonus, competitive equity package, and benefits. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience.</p> <h3><strong>In this role, you can expect to:</strong></h3> <ul> <li>Support analytics and measurement for lending initiatives, including tracking performance and key metrics across the funnel</li> <li>Experience in experimentation, statistical analysis, and measurement to guide decision making.</li> <li>Contribute to product roadmap, analysis and metric ideation, and strategic discussions with stakeholders.</li> <li>Build and maintain dashboards and recurring reporting to monitor lending health and business trends</li> <li>Partner with Product, Risk, Finance, Marketing, and Data teams to understand analytical needs and deliver timely insights</li> <li>Strong stakeholder management skills, with a record of working cross-functionally to achieve results</li> <li>Collaborate with analysts and other functions to help bridge business questions and technical (data / computational) solutions.</li> </ul> <h3><strong>To thrive in this role, you have:</strong></h3> <ul> <li>2–4 years of experience in data analytics, product analytics, financial analytics, or a related field</li> <li>Strong SQL skills and experience working with data visualization tools such as Looker or Tableau</li> <li>Working knowledge of Python or R for analysis (or strong interest in developing these skills)</li> <li>Familiarity with experimentation concepts, statistical analysis, and basic causal thinking</li> <li>Strong communication skills and the ability to collaborate effectively with cross-functional partners</li> <li>Curiosity, attention to detail, and a desire to learn and grow as an analyst</li> </ul> <p>#LI-AM1 #LI-HYBRID</p><div class="content-conclusion"><h2><strong>A little about us</strong></h2> <p>At Chime, we believe that everyone can achieve financial progress. We created Chime—a financial technology company, not a bank*—on the premise that core banking services should be helpful, easy, and free. Through our user-friendly tools and intuitive platforms, we empower our members to take control of their finances and work towards their goals. Whether it's starting a savings account, purchasing a first car or home, launching a business, or pursuing higher education, we're proud to have helped millions unlock their financial potential.</p> <p>We're a team of problem solvers, dreamers, and builders with one shared obsession: our members. From day one, Chimers have worked tirelessly to out-hustle and out-execute competitors to bring our mission to life. Their grit and determination inspire us to work harder every day to deliver the very best experience possible. We each bring an owner's mindset to our work, refusing to be outdone and holding ourselves accountable to meet and exceed the highest bars for our teams, our company, and our members.</p> <p>We believe in being bold, dreaming big, and taking risks, while also working together, embracing our diverse perspectives, and giving each other honest feedback. Our culture remains deeply entrepreneurial, encouraging every Chimer to see themselves as stewards of our mission to help everyday Americans unlock their financial progress. </p> <p>We know that ... (truncated, view full listing at source)
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