Senior Data Scientist, Membership

About the role

In this role you will define how Chime measures membership value and the drivers of direct-deposit retention — and lead the strategic analyses that shape decisions made by senior leaders across the company. Chime's Membership XFN owns end-to-end DD retention by making membership more valuable, more flexible, and more resilient across the member lifecycle, spanning tiering and eligibility, benefits and value realization, tier transitions, retention/resurrection, and resilience experiences that support members through transitions like job loss. You'll set the agenda for understanding how members experience and realize value from their membership, 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 retention and value-realization metrics move but shape the strategy your partners pursue in response. This is a role where you'll think holistically about the member lifecycle, 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 membership metrics — the definitions, methodology, and read-outs that other analytics teams and stakeholders across Product, Engineering, Design, Marketing/LCM, Risk, and Research rely on as the source of truth, with DD Retention as the north star and membership value realization, retention, and tier-related outcomes as supporting metrics.
• Set the strategy for how Chime understands membership tiering and eligibility, benefit value realization, tier transitions, and resilience experiences. Unlike anyone else, you will anticipate changes in how members move through the lifecycle, 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 for how the organization understands DD retention and membership value across the Benefits, Expansion/Eligibility, and Resilience/In Between Jobs squads.
• Partner widely and at altitude. You'll be a strategic thought partner to leaders across Product, Engineering, Design, Marketing/LCM, Risk, and Research — pressure-testing what's worth doing, not just answering the questions handed to you. The stronger these partnerships, the more successful you and Chime will be.
• Ask why a lot, and raise the bar for those around you. Your proactive inquisitiveness, supported by your data dexterity, means you lead first-of-its-kind analyses and mentor the data scientists around you to do the same.

To thrive in this role, you have

• 5-7 years in data-focused roles, leading analyses or building data tools that shape the decisions of an executive audience and frame the trade-offs leaders weigh.
• Deep proficiency in retention and lifecycle metrics — engagement, value realization, tier transitions, and the leading indicators of member resilience — enough to set the narrative, not just report it. Familiarity with measuring membership or subscription-style value across a lifecycle is a strong plus.
• Extensive stakeholder management experience at the Director/VP+ altitude, and a clear Northstar for how Analytics partners with and influences product, engineering, and risk teams.
• Expertise in SQL — you innately translate business questions to queries, understand the edge cases of joins, and with dexterity explore a warehouse to find data most appropriate to the problem.
• Analytics engineering depth — you have built data models in dbt that you and others rely on, and you set standards for how the team creates durable data products.
• Sound statistical inference skills, with the ability to communicate uncertainty appropriately to senior business partners and raise the methodological bar for others. Experience designing and interpreting experiments (A/B tests) is valued.
• A focus on impact — you don't stop with just recommendations but ensure to see work through to changing the product, and you multiply that impact by mentoring the data scientists around you.

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