Marketing Senior Data Scientist, Gemini Marketing

Google's leadership team hand-picks thorny business challenges, and members of BizOps work in small teams to find solutions. As part of this team you fully immerse yourself in data collection, draw insight from analysis, and then zoom out to develop compelling, synthesized recommendations. Taking strategy one step further, you also persuasively communicate your recommendations to senior-level executives, roll-up your sleeves to help drive implementation and check back-in to see the impact of your recommendations.

We are seeking a Senior Data Scientist to lead the technical measurement and optimization engine for Gemini App Marketing. In this role, you will apply advanced statistical modeling, machine learning, and causal inference to solve complex growth challenges. You will move beyond traditional analytics to build predictive frameworks for user lifetime value (LTV), churn, and incrementality.

As a Senior DS, you will be the technical lead on experimental design, ensuring our marketing investments are mathematically sound and scientifically validated. You will partner with product data science and engineering to bridge the gap between marketing triggers and product telemetry, building scalable data pipelines and automated model deployments that drive high-velocity decision-making.

Responsibilities

• Lead the design and analysis of sophisticated controlled experiments (A/B tests) and quasi-experiments to isolate the true incremental impact of Gemini marketing programs.
• Develop and deploy machine learning models to forecast key business drivers, including user lifetime value, churn propensity, and adoption curves.
• Partner with media teams to integrate data science outputs into bidding and targeting strategies. Build "agentic" or automated workflows that utilize AI to optimize campaign performance and marketing OpEx.
• Use multivariate analysis and sequence modeling to identify the golden paths in the user journey—predicting which specific feature interactions lead to long-term retention and Daily Active User (DAU) growth.
• Build and prototype robust data pipelines and analysis frameworks in BigQuery. Advocate for data infrastructure improvements and ensure the scalability of data science products across the marketing organization.

Minimum qualifications:

• Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
  
• 4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
  

Preferred qualifications:

• PhD in a quantitative discipline (e.g., Statistics, Econometrics, or related).
• Experience building or leveraging agentic frameworks and LLM-powered automation to enhance analytical velocity.
• Experience with Media Mix Modeling (MMM), Multi-Touch Attribution (MTA), or advanced incrementality testing at scale.
• Experience working directly with product engineering to implement tracking schemas and event-logging for complex user flows.
• Understanding of iOS/Android measurement nuances, including privacy-centric attribution (SKAN, Privacy Sandbox) and mobile-first growth loops.