Minimum qualifications:

• Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
  
• 10 years of 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 taking projects from ambiguous concepts to finished, high-quality data products within a cross-functional unit.
• Experience navigating e-commerce or marketplace data, including an understanding of merchant behaviour and consumer life-cycles.
• Experience in SQL, with the ability to build maintainable data workflows and statistical models.

About the job

Help serve Google's worldwide user base of more than a billion people. Data Scientists provide quantitative support, market understanding and a strategic perspective to our partners throughout the organization. As a data-loving member of the team, you serve as an analytics expert for your partners, using numbers to help them make better decisions. You will weave stories with meaningful insight from data. You'll make critical recommendations for your fellow Googlers in Engineering and Product Management. You relish tallying up the numbers one minute and communicating your findings to a team leader the next.

As a Staff Data Scientist, you are a lead architect for the mission to build scalable, commercially focused, and machine consumable data products and insights that simplify problems and drive outcomes for merchants and consumers. You bridge the gap between complex datasets and business goals, across high-impact, cross-functional teams.

Operating with high autonomy, you solve the organisation’s most unclear and meaningful problems rather than being tied to a single product silo. You are a leader in the analytics community, ensuring work is reliable and high-quality to deliver lasting solutions.

As a Technical Lead, you are accountable for others in defining valuable goals and ensuring projects deliver clear business results. You act as a key partner to Engineering and Product leaders, helping shape the direction of our AI data products within our "one-team" model.

We take pride in our ability to make complex things simple and tell clear stories through data. As a senior leader in this team, you will have a global impact, contributing to Google’s high-profile agentic AI initiatives.

Users come first at Google. Nowhere is this more important than on our Advertising and Commerce team: we believe that ads and commercial information can be highly useful to our users if that information is relevant to what our users wish to find or do. Advertisers worldwide use Google Ads to promote their products; publishers use AdSense to serve relevant ads on their website; and business around the world use our products (like Google Shopping, and Google Wallet) to support their online businesses and bring users into their offline stores. We are constantly innovating to deliver the most effective advertising and commerce opportunities of tomorrow.

Responsibilities

• Technical Leadership and Solving Ambiguity: Lead high-stakes projects with unclear goals, mentoring junior data scientists to define high-value problem statements and deliver measurable business impact.
• Scalable Product Innovation: Build commercially focused, self-serve data products and AI-automated insights that move beyond traditional dashboards for merchants and shoppers.
• Strategic Advising: Consult with Engineering and Product leaders, providing data-driven perspectives on product direction and identifying new opportunities grounded in data.
• Metric Design and Infrastructure Advocacy: Define key metrics and attribution mechanisms while advising data engineering on infrastructure optimisations for "machine-consumable" insights.
• Radical Transparency: Advocate data integrity across product areas, reducing organisational paralysis through clear, data-backed conversations with senior leadership.