Senior Research Data Scientist, Platform

Position: Senior Research Data Scientist, Payments Platform
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Minimum qualifications:

* Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.

* 5 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 3 years of work experience with a PhD degree.

* 5 years of experience using Python for statistical programming.

Preferred qualifications:

* 8 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree.

About the job

Google Payments is a priority and a massive opportunity for Google to redefine digital commerce. As the foundational platform for most Google products-including Ads, You Tube, Play, and Cloud-we are at the heart of every commerce transaction mediated or fulfilled by Google. Our team supports a dynamic, multi-sided ecosystem that connects billions of users with financial institutions, global networks, and both first-party and third-party merchants.

By facilitating safe and seamless commerce, we drive higher conversion rates and reduce fraud, which in turn accelerates the growth of the global digital GDP. This enables Google and our partners to deliver unprecedented value to the world economy. With a global mandate to serve users across both developed and emerging markets, you will apply advanced research and statistics to solve issues at an immense scale.

Join us in building the next generation of payment experiences that are easy, fast, and consistent for everyone, everywhere.

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

US: $174000 - $253000 (USD) + 15% bonus target + bonus + equity + benefits

Learn more about benefits at Google.

Responsibilities

* Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions to answer. Provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models.

* Use custom data infrastructure or existing data models as appropriate, using specialized knowledge. Design and evaluate models to mathematically express and solve defined problems with limited precedent.

* Gather information, business goals, priorities, and organizational context around the questions to answer, as well as the existing and upcoming data infrastructure.

* Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Independently format, re-structure, and/or validate data to ensure quality, and review the dataset to ensure it is ready for analysis.