Staff Data Scientist, Marketing Analytics

About the role

When people sign up for Chime, we want to know which marketing efforts brought them in and which ones brought in members who stay and use their account. You will set the direction for how Chime answers that question.

You will be the senior analytics leader for paid marketing. You will decide how we measure a very large paid media budget and how that measurement turns into spending decisions. This is a high-visibility role. Marketing, Growth, Finance and executive leaders will treat your work as the main reference for how marketing performs. You will join the Marketing Analytics team and work across Marketing, Finance, Data Engineering and Data Science/ML.

In this role, you can expect to

• Own the paid performance story. Track spend and results across channels every week. Explain why numbers moved, in plain words that a non-analyst can act on.
• Measure new-member offers. Show whether our sign-up offers bring in better members and whether they are worth the cost. Compare offer groups against fair, matched groups.
• Set the bar for experiments and offers. Define how tests are designed and read, and how we decide whether sign-up offers are worth the cost.
• Improve how we give credit to marketing channels. Find where our attribution rules fall short, propose better ones, and work with Data Engineering to build and maintain them.
• Turn marketing mix modeling into budget advice. Use the output of our Marketing Mix Model to advise Marketing on how to allocate budget across channels.
• Help plan the work ahead. Estimate the likely impact of new marketing ideas so the team can prioritize.
• Use AI to work faster and go deeper. Use AI tools to speed up analysis, check your work, and build things others can reuse.
• Raise the level of the team. Coach senior data scientists, guide contractors and set the quality bar for high-stakes work.

To thrive in this role, you have

• A Bachelor’s degree and 10+ years of experience in analytics or data science, with deep experience in marketing, growth or consumer products
• A track record of setting measurement strategy across several teams, not only delivering analyses within one team
• Deep expertise in marketing measurement: attribution, incrementality, MMM, cost per acquisition and LTV:CAC, including designing these systems from scratch
• Expert-level experimentation and causal inference skills, including knowing when standard methods don’t fit and building approaches that do
• Strong SQL and experience shaping data models and pipelines in large data warehouses (we use Snowflake)
• Advanced Python or a similar language for analysis
• Experience using Marketing Mix Model output to guide budget decisions at significant scale
• Hands-on experience bringing AI tools into analytics work for a team, and good judgment about their limits
• A history of influencing VP-level and executive decisions without formal authority, including settling disagreements between competing stakeholders
• Clear writing and speaking for senior, non-technical audiences
• A track record of growing other senior data scientists’ skills through mentorship, frameworks and shared tools
• Comfort with problems that have no precedent, where you have to define both the question and the approach

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