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 a Product Data Scientist for FOP Optimization, you will shape Payments products and solutions, helping our leaders make data-driven decisions. You will lead a critical part of the payments routing infrastructure, Smart Router, that utilizes machine learning and AI to process first-party transactions across Play, YouTube, Ads, and more. You will drive analytics for the form of payment (FOP) optimization, building on success metrics, driving insights, and driving global launches. You will also play a critical role in our interactions on Business-to-Consumer (B2C) analytics with Play and YouTube to optimize buyflows, purchase readiness, conversion, and UI on these critical Google products.
Responsibilities
- Play a critical role in shaping the future of Google Payments by leveraging data and analytics to drive decisions, influencing strategy, and creating business impact across the organization.
- Identify and solve ambiguous, high-stakes problems, transforming data into clear insights that directly influence leadership decisions (e.g., VPs and directors).
- Lead complex projects that combine analytical precision with organizational strategy, delivering clear insights that inform tangible business decisions.
- Contribute to the development and alignment of team objectives and key results and analytics strategy to ensure they support broader 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.
Qualifications
Minimum qualifications:
- Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, a related quantitative field, or equivalent practical experience.
- 8 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL), or 5 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.
- 10 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).
- Experience in product analytics within payments, e-commerce, or financial services.
- Ability to take initiative in unstructured environments with a bias for action and sharp attention to detail.