Backed by SoftBank VF, ICONIQ and Menlo.
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. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- A Bachelor’s degree and 8+ 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
More about this 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 co-own and help decide how we measure a 9 figure plus paid media budget and how that measurement turns into optimization and allocation 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.
- 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.
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