Senior Staff Product Data Scientist, Merchant...

As a part of the Senior Staff Data Scientist, you will lead the technical evolution of our data systems across Google’s merchant and communication products. Your role focuses on Business Agents, Google Business Profiles, and Business Messaging surfaces that connect consumers with millions of businesses daily.

In this role, you are expected to operate fluidly between data science and software engineering. You will not just run analyses but will build the systems that perform them. You will move away from manual SQL pulls and static dashboards. Your mandate is to build self-healing data pipelines, establish an AI-readable semantic layer, and develop autonomous agents capable of running full exploratory analyses.

Your technical work must drive measurable business impact, bridge the gap between complex infrastructure and product execution turning interaction data into clear, actionable insights that dictate what we build next. Your work will directly influence merchant Return on Investment (ROI), optimize consumer messaging funnels, and ensure our AI agents deliver tangible value to the businesses that rely on Google.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $240000 - $334000 (USD) + 25% bonus target + equity + benefits

Learn more aboutbenefits at Google (https://www.google.com/about/careers/applications/benefits/) .

Responsibilities

• Develop AI agents capable of executing end-to-end data analysis, from exploring interaction data in Business Profiles and writing queries, to diagnosing metric shifts and generating product recommendations.

• Build and deploy production-code data pipelines for Business Messaging and Business Agents.

• Structure data warehouses so that they are universally readable by internal AI systems and product surfaces, ensuring accurate, reliable, and reproducible query retrieval.

• Architect the statistical frameworks and infrastructure for A/B testing, and build automated systems that interpret experimental results, flag statistical noise, and output clear ship/no-ship recommendations.

• Serve as a technical benchmark for the data organization by writing clean, maintainable code (Python, SQL), and mentor senior team members on system architecture and advanced statistical methods.

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Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See alsoGoogle’s EEO Policy (https://www.google.com/about/careers/applications/eeo/) ,Know your rights: workplace discrimination is illegal (https://careers.google.com/jobs/dist/legal/EEOC_KnowYourRights_10_20.pdf) ,Belonging at Google (https://about.google/belonging/) , andHow we hire (https://careers.google.com/how-we-hire/) .

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Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

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Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.

Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders; deep expertise in domain., + Bachelor’s degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.

• 13 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) (or 10 years work experience with a Master’s degree).

Preferred qualifications:

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

• 15 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).