We’re looking for a Senior Data Scientist to be the dedicated analytics partner to Chime’s Investor Relations and Corporate Strategy teams. As a public company, Chime reports its performance to the investor community every quarter, and that story has to rest on data that is accurate, consistent, and well understood. You’ll build a holistic view of how the business is performing, use internal data to help Chime communicate its progress through earnings and public disclosures, and bring analytical rigor to high-priority, high-visibility projects that shape Chime’s strategic direction. This is a highly cross-functional role. You’ll work with teams across Chime, from Finance and Product to Marketing, Risk, and Operations, to understand what drives performance in every part of the business and how to measure it. It is not an experimentation-focused role: the work centers on business performance, financial and operating metrics, and strategic analysis rather than A/B testing. You’ll thrive here if you pair a high bar for precision with the agility to move quickly as priorities shift. In this role, you can expect to Build a holistic, company-wide view of Chime’s performance, connecting member growth, engagement, and product usage to the financial and operating metrics that matter most to the business. Partner with Investor Relations to turn internal data into how Chime communicates its progress to investors, supporting quarterly earnings materials, shareholder communications, and public disclosures. Be an arbiter of truth with data, making sure the metrics Chime shares externally are precisely defined, consistent across sources, and able to withstand scrutiny. Explain why metrics move. Spot trends and inflection points early, dig into the underlying drivers, and turn findings into clear narratives for senior leaders. Partner with Corporate Strategy on high-priority, high-visibility projects with strategic impact for Chime, bringing structure and data to ambiguous, open-ended questions. Work across every part of Chime, partnering with Finance, Product, Marketing, Risk, Operations, and other Analytics teams to understand how each area operates and how its performance should be measured. Deliver high-stakes analyses on tight timelines, such as during earnings cycles, without compromising accuracy. Build durable, reusable data models and reporting so recurring questions get answered consistently and efficiently.
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Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed