Director, Data Science, Personalization, Gemini App, DeepMind

Google · Mountain View, CA, USA

As 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.

Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.

We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.

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.

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.
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