Minimum qualifications:- Bachelor's degree in Data Science, or similar technical field of study, or equivalent practical experience.
- 15 years of professional experience as an data science leader.
Preferred qualifications:- Master's degree or PhD in Data Science, Statistics or related field.
- Experience in Generative AI model training and development, large-scale consumer product development, or other AI/ML research and foundations.
- Ability to influence decision making at the director level, aligning incentives across multiple stakeholders.
- Track record of establishing a data-driven culture through infusing critical measurement and analysis into the team's operations.
About the jobAs the Personalization Data Science Director for GeminiApp, you will be responsible for creating a personalized AI experience for our users. This critical role requires a leader capable of navigating novel and highly ambiguous problems in a fast-paced environment. You will drive a strategic shift in our operations, evolving our understanding of performance beyond isolated metrics to a holistic view that connects development directly to long-term product success. You will enable our product and engineering teams to release high quality features and move fast by developing personalization measurements and insights that drive user growth.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $384000 - $428000 (USD) 30% bonus target bonus equity benefits
Learn more about benefits at Google .
Responsibilities- Define and lead a strategic shift in personalization measurement, moving beyond isolated metrics to a holistic framework, including online metrics and offline eval's that reflect what drives value for our users and product success.
- Influence senior stakeholders across disparate organizations to align GeminiApp's personalization strategy with rigorous insights, navigating conflicting priorities to ensure OKRs reflect true long-term user value rather than just immediate short-term signals.
- Partner closely with Engineering, Product, and UX leaders to drive innovation velocity while maintaining rigorous quality standards in a fast-paced, highly ambiguous environment.
- Mentor and develop a high-performing AI Data Science team capable of thriving in ambiguity and leading complex, novel projects.
