About the job

Applied Research and Strategy is responsible for horizontal analysis and methodology development to maximize the impact and inform knowledge and information most important strategic decisions. We drive strategic insights for knowledge and information leaders across external landscape, growth and our biggest long term bets. We develop cross-knowledge and information data science strategies and approaches, create cross-product metrics and ensure data quality and push the envelop on new methodologies and tools to enable insights.

The mission of Data Science Applied Research and Strategy is to drive from data insights to strategic cross-product area decision making. In this role, you will partner with the knowledge and information ecosystems team to understand the state and trends in the content ecosystem, identify ways in which Google can continue to support the ecosystem to ensure the existence and access to the content and data necessary to power our products and serve our users. To support this new product area, you will develop new metrics and data sources, develop foundational understanding of the ecosystem, and generate insights and provide direction to product, engineering and partnerships strategies.

You will be a core member of a close and collaborative cross-functional group across product management, engineering, UXR, and partnerships. You will utilize and develop your technical data science expertise, strategic product insight, cross-functional collaboration, and executive influence and communications.

The US base salary range for this full-time position is $163,000-$237,000 + 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

• Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying advanced investigative methods as needed. Conduct end-to-end analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.

• Build and prototype analysis pipelines to provide insights at scale. Develop a comprehensive understanding of Google data structures and metrics, advocating for changes where needed for both products development and sales activity.

• Interact cross-functionally with a wide variety of people and teams. Work closely with engineers to identify opportunities for, design, and assess improvements to Google products.

• Make business recommendations (e.g., cost-benefit, forecasting, experiment analysis) with effective presentations of findings at multiple levels of stakeholders through visual displays of quantitative information.

Minimum qualifications

• Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.

• 8 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL), or 5 years of experience with a Master's degree.

Preferred qualifications

• Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.

• Experience in data science methodologies, data analysis, and experimental design.

• Ability to think critically, analyze complex problems, and develop data-driven solutions.

• Ability to articulate complex concepts to both technical and non-technical stakeholders.

• Ability to influence decision-making and drive change.

• Excellent business acumen and the ability to align research efforts with organizational objectives.