The opportunity
SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary…
What you'll do
Build and own the measurement layer for performance marketing: economics and performance by channel, campaign, audience, geo, and creative, across both PLG and Sales-Led revenue lines
Design incrementality tests (geo, audience, and conversion lift) with channel: owners, and use the results to move budget and calibrate attribution, not just to fill a slide
Stand up and maintain our media-mix model, and pair it with test results to: answer the big allocation questions: which channels to scale, which to cut, and where we're hitting saturation
Own the quality of the predictive LTV signal we send to Meta, Google, and the: other networks: validate it against realized revenue, catch drift and breakage early, and partner with Data and Engineering to improve it
Keep pipeline source and campaign attribution separate and clean, so: self-reported source, promo codes, click-based attribution, and CRM pipeline each answer their own question without double counting revenue
You have 7+ years of experience in marketing analytics, marketing science, or: data science supporting paid acquisition
What they're looking for
- You have strong SQL and python skills and are comfortable building both data pipelines and predictive models
- You've run hold-out or incrementality tests and worked with MMM and: attribution models in production, and you know the limitations of each
- You understand how ad platforms report, optimize, and ingest conversion: signals, and you don't take platform-reported numbers at face value
- You communicate clearly with channel managers, Finance, and leadership, and: you're honest about what the data does and doesn't support