Product Data Scientist, Platform

Minimum qualifications

• Bachelor's degree in statistics, mathematics, data science, engineering, physics, economics, a related quantitative field, or equivalent practical experience.
• 5 years of work experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems) and coding (Python, R, SQL) OR 2 years work experience with a Master's degree.

• Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
• Experience working on statistical/casual inference techniques across experimentation and observational studies.
• Experience working in the payments, online ecommerce, or marketplace industry.

The Payments team builds and operates Google’s monetization infrastructure that enables all Google products to monetize. This monetization engine moves across countries and supports various business models including B2B, B2C, subscriptions, and marketplaces.

The Identity and Risk teams safeguard Google’s platform by developing solutions to mitigate fraud, abuse, and identity threats. The Identity team focuses on high‑assurance verification and frictionless user onboarding, while the Risk team builds infrastructure necessary to manage financial risk and prevent wide‑scale platform abuse. Together, they enable trusted global commerce by balancing platform protection with seamless experiences.

As a Data Scientist, you will bring excellence and innovation to how analytics is done—leveraging Gen AI tools for data exploration and workflow automation while maintaining high standards of experimental design. You will balance multiple high‑stakes initiatives, diving into technical details while keeping a sharp eye on the broader strategic goals of both the Identity and Risk organizations.

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

US: $138,000 - $198,000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

• Perform analysis by utilizing relevant tools (e.g., SQL, R, Python). Using comprehensive technical knowledge, use custom data infrastructure or existing data models.
• Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Format, re‑structure, and validate data to ensure quality.
• Report key performance indicators (KPIs) to support business reviews with cross‑functional/organizational leadership team. Translate analysis results to business insights or product improvement opportunities.
• Provide analytical insights and recommendations to influence product feature development decisions, with some guidance.
• Build and prototype analysis and business cases iteratively to provide insights elop comprehensive knowledge of Google data structures and metrics.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law.

If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.