Data Scientist, Product, 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.

As the key analyst on Forms of Payments (FOPs) and Business-to-Consumer (B2C) analytics, you will shape Payments products and solutions, helping our leaders make data-driven decisions. You will lead a critical part of Payments that focuses on acquiring the usage of nearly one billion users with FOPs across all Google Surfaces. You will drive analytics for FOPs launches globally, improving cards and non cards types, driving transaction performance, capturing the Quality and Value from FOPd users, as well as managing FOPs Risk and Compliance. You will also play an important role in our interactions on B2C analytics with Play and You Tube to improve Buyflows, Purchase Readiness, Conversion and UI on these critical Google products.

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 problems, transforming data into insights that influence leadership decisions.
• Lead projects that align with the organizational strategy, deliver insights that help business decisions.
• Contribute to the development and alignment of team Objectives and Key Results (OKRs) and analytics strategy to ensure they support the product and business goals across the Payments organization.
• Collaborate cross-functionally with product, engineering, and operations teams to define key metrics and support data-driven decision-making.