Product Data Scientist, Payments Platform Experience

Google•Mountain View, CA

6d•$138,000 - $198,000•Remote

About The Position

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 an 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.

Requirements

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.

Nice To Haves

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.

Responsibilities

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, and with some guidance.
Build and prototype analysis and business cases iteratively to provide insights at scale. Develop comprehensive knowledge of Google data structures and metrics.