Product Data Scientist, Payments

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. Whether it is paying online with Autofill, using tap and pay in stores, or using the Google Pay app, the Payments team at Google is focused on making payments simple, seamless, and secure. In addition to consumer payment technologies, the Payments team also powers the money movement between Google and its consumers and businesses. Responsibilities

Shape the future of Google Payments by leveraging data and analytics to drive decisions, influence strategy, and create business impact across the organization.

Identify and solve ambiguous, high-stakes problems, transforming data into clear, actionable insights that directly influence leadership decisions (e.g., Vice Presidents (VP) and Directors).

Lead complex projects that combine investigative excellence with organizational strategy, delivering clear and actionable insights that inform tangible business decisions.

Become a strategic thought partner to stakeholders across product, engineering, and executive leadership, influencing key decisions at multiple levels.

Contribute to the development and alignment of team Objectives and Key Results (OKRs) and analytics strategy to ensure they support broader product and business goals across the Payments organization.

Qualifications

• Minimum qualifications:

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

• 5 years of experience with analysis applications (e.g., extracting insights, performing statistical analysis, or solving business problems), and coding (e.g., Python, R, SQL), or 2 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.