Staff Product Data Scientist, Digital Media

The Waymo Product Data Science team is seeking a Growth and Experience Lead to connect marketing performance to real business outcomes. This role will build ROI methodologies and efficiency guardrails that leadership can act on, own optimization across the full acquisition picture, and lead deep-dive analyses.

Responsibilities

• Own optimization across the full acquisition picture — brand media, performance channels, promotions, and referrals — not just the parts with clean attribution
• Build Waymo's incrementality measurement program, including geo-based holdout tests, switchback experiments, and media mix modeling across every acquisition channel
• Build Waymo's LTV and CAC framework and use it to guide how marketing spend gets allocated
• Lead deep-dive analyses across geos, audiences, creatives, and channels to find the non-obvious growth levers nobody's looked for yet

Requirements

• At least 6 years of industry experience, with a strong focus on growth marketing, including time spent owning measurement strategy, not just executing it
• A track record of working directly with marketing leadership as a trusted partner
• Proficiency in SQL and Python or R for data manipulation, statistical modeling, and experiment analysis
• Hands-on experience designing and analyzing incrementality experiments — geo holdout tests, switchback designs, or intent-to-treat analyses — in a consumer tech, marketplace, or rideshare context
• Strong causal inference fundamentals — you know how to design studies that produce actionable, credible results

Preferred

• Experience with media mix modeling (MMM) or multi-touch attribution (MTA) in addition to geo-based incrementality testing
• Experience building LTV and CAC frameworks and using them to guide real spend decisions
• Familiarity with paid media platforms and channel dynamics (SEM, paid social, programmatic)

The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.