Chime Staff Data Scientist, Marketing Analytics at Chime leads analytics for paid marketing measurement and optimization. Responsible for setting measurement strategy and advising on budget allocation using advanced marketing mix modeling.
Responsibilities
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.
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 introductory new member 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 credit 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.
Be a proactive business partner. Work with Marketing, Growth and Finance leaders as a trusted partner. Share insights and recommendations before they ask, and help them decide what to do next.
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 8+ years of experience in analytics or data science, with deep experience in marketing, growth or consumer products
Qualification
Bachelor’s degreeDeep experience in marketing
Required
Bachelor’s degree
10+ years of experience in analytics or data science
Deep experience in marketing, growth or consumer products
Track record of setting measurement strategy across multiple teams
Expertise in marketing measurement including attribution, incrementality, MMM, cost per acquisition, and LTV:CAC
Expert-level experimentation and causal inference skills
Strong SQL and experience with large data warehouses (Snowflake)
Advanced Python or similar language for analysis
Experience using Marketing Mix Model output to guide budget decisions
Hands-on experience with AI tools in analytics
History of influencing VP-level and executive decisions
