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Senior Data Scientist, AI & App Experience

Chime Financial, Inc·US·San Francisco, CA, USA·senior
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About the role In this role you will define how Chime measures the experience members have in the app and the impact of its AI-powered features — and lead the strategic analyses that shape decisions made by senior leaders across the company. Chime's members interact with the app daily and increasingly through AI-driven experiences. You'll set the agenda for understanding how members engage with these experiences, what's working and what isn't, and what those signals mean for Chime's product and business — framing the questions others aren't yet asking. By driving deep dive analysis on the trends you uncover in Chime's data, you'll not only explain why engagement and experience metrics move but shape the strategy your partners pursue in response. This is a role where you'll think holistically about the Chime app and AI experience, operate as a strategic partner to leaders across the company, and still be in the data to discover the story behind the metrics. The base salary offered for this role and level of experience will begin at $133,000 and up to $185,000. 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. In this role, you can expect to Define and own the measurement framework for Chime's AI and App Experience metrics — the definitions, methodology, and read-outs that other analytics teams and stakeholders across product, design, engineering, and member services rely on as the source of truth. Set the strategy for how Chime understands engagement, adoption, and the quality of its AI-powered features. Unlike anyone else, you will anticipate changes in how members interact with the app and AI experiences, build the understanding for why, and shape what leaders do in response. Be the arbiter of truth with data. You'll raise the methodological bar for the highest-stakes analyses and define what "good" looks like