Staff Product Data Scientist, Pixel
Google•Published 2 hours ago•First seen 2 hours ago
Google Pixel phones, watches, and earbuds showcase the best of Google’s hardware and AI. We develop technologies to make user experiences faster, more powerful, and seamless including industry leading camera features powered by Google’s expertise in Artificial Intelligence and Machine Learning.
The Pixel Data Science team's mission is to power the growth and evolution of the Pixel ecosystem. We bridge data, analytics, and business strategy, acting as essential thought partners to product and strategy leaders within the centralized Devices and Services Strategy and Operations (StratOps) organization. By uncovering critical insights and developing data-driven solutions, we optimize performance, enhance user experiences, and help scale the Google Pixel business.
In this role, you will provide business critical insights, leveraging data to influence the direction of products. Your work will directly contribute to key decisions and the overall success of the Pixel line.The US base salary range for this full-time position is $183,000-$271,000 + 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.
The Pixel Data Science team's mission is to power the growth and evolution of the Pixel ecosystem. We bridge data, analytics, and business strategy, acting as essential thought partners to product and strategy leaders within the centralized Devices and Services Strategy and Operations (StratOps) organization. By uncovering critical insights and developing data-driven solutions, we optimize performance, enhance user experiences, and help scale the Google Pixel business.
In this role, you will provide business critical insights, leveraging data to influence the direction of products. Your work will directly contribute to key decisions and the overall success of the Pixel line.The US base salary range for this full-time position is $183,000-$271,000 + 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
- Perform analysis on key Pixel metrics utilizing advanced investigative tools (e.g., SQL, R, Python). Own and execute the full workstream for Pixel dashboards, including data engineering, dashboard design, metrics definition, and insights sharing.
- Own outcomes for projects by covering problem definition, metrics development, data extraction and manipulation, visualization, creation, and implementation of statistical models, and presentation to stakeholders.
- Develop solutions for ambiguous problems lacking clear precedent by framing hypotheses and providing recommendations that combine investigative and product-specific expertise.
- Liaise and align cross-functionally with Product Management, Marketing, Sales, and Executive leadership to translate analytics into actionable business solutions.
Minimum qualifications:
- Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
- 10 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) or 8 years of work experience with a Master's degree.
- Experience building predictive or causal models to understand user behaviors (such as churn, loyalty, engagement, etc.).
Preferred qualifications:
- Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
- 12 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).