Data Scientist, Marketing

Cursor; San Francisco (CA); Presencial; USD 140.000 - 210.000; Jornada completa

Descripción de la vacante

SpaceXSI is seeking a senior data/marketing analytics leader to own measurement for performance marketing across 10+ channels and the full portfolio of AI products. You will build scalable measurement, design incrementality tests, and maintain a media-mix model to guide budget decisions and allocation strategy.

You will own predictive LTV signals sent to Meta, Google, and other networks, ensuring they align with realized revenue and catch drift early.

Formación

• 7+ years in marketing analytics, marketing science, or data science for paid acquisition.
• Strong SQL and Python skills, building data pipelines and predictive models.
• Experience with hold-out/incrementality tests, MMM, and attribution models.
• Understand ad platform reporting, optimization, and conversion signals.

Responsabilidades

• Build and own the measurement layer for performance marketing across channels and revenue lines.
• Design incrementality tests with channel owners and use results to adjust budgets and attribution.
• Stand up and maintain a media-mix model and interpret results for channel allocation.
• Own the quality of predictive LTV signals sent to networks, validate against revenue, and monitor drift.
• Keep pipeline source and attribution separate and avoid double counting revenue.

Conocimientos

Marketing analytics

SQL

Python

Incrementality testing

Descripción del empleo

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 and expanding consciousness to the stars.

SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next.

About the role

The Data team at SpaceXSI is a small team that works across the company to inform business and product decisions, and we're hiring the first member of our team to focus fully on marketing. Performance Marketing at SpaceXSI drives scaled acquisition across 10+ channels for Grok, Grok Bot, and our full portfolio of AI products, across consumer, SMB, startup, and enterprise audiences.

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 may be a fit if

• - You have 7+ years of experience in marketing analytics, marketing science, or data science supporting paid acquisition
• - 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
• - You're self-directed, comfortable owning ambiguous problems end to end