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- Bachelor’s degree in a quantitative field (e.g., Statistics, CS, Economics, Engineering) or equivalent practical experience.
- 15 years of experience in data science, analytics, or product strategy.
- 8 years of people management experience.
- Experience driving the development, evaluation, and commercialization of AI/ML products.
- Experience managing managers and leading multi-functional organizations.
- Experience implementing these in a production environment.
- Understanding of growth and retaining drivers.
- Deep technical understanding of LLMs, Generative AI, and enterprise AI use cases, with the ability to translate complex model performance data into actionable product strategy.
- Ability to synthesize technical data complexity into a simple, compelling narrative that shifts the perspective of C-suite executives.
- Ability to frame ambiguity into tractable analytical problems for the team.
- Proven track record of defining and driving data science and analytics for a global product or business unit.
The US base salary range for this full-time position is $307,000-$427,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google .
Responsibilities
- Create a proactive leadership model for a new data science and analytics function to identify market shifts and user behavior trends.
- Drive the vision for a "zero-latency" insight culture. Oversee the development of automated, self-service intelligence platforms that empower thousands of stakeholders to make data-driven decisions.
- Establish the standard for experimentation. Act as the final authority on complex causal inference problems and decisions for high-stakes product launches.
- Serve as an advisor to cross-functional leaders to define evaluation criteria and growth strategy for Generative AI and ML products.
- Secure cross-functional buy-in for data-driven pivots. Stop underperforming projects and reallocate resources based on performance data, navigating complex political landscapes.
Key Skills
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