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X Note: By applying to this position you will have an opportunity to share your preferred working location from the following:
Mountain View, CA, USA; New York, NY, USA.
Minimum qualifications:
- Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
- 5 years of experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems), and coding (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.
About the job
Google for Education is transforming teaching and learning at scale by bringing the best of Google technology to students, teachers, and education leaders.
The Education Data Science team plays a fundamental role in the success of Google for Education, by providing an understanding of our business and product performance and developing insights to help drive strategic decisions.
Education is currently experiencing a seismic shift in the role of technology, with a multi-year acceleration of adoption and growth. In this role, you will have an opportunity to shape Google's education products and business, and help transform education at Google scale.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $138000 - $198000 (USD) 15% bonus target equity benefits
Learn more about benefits at Google .
Responsibilities
- Define, own and evolve product/business success metrics. Report, analyze and forecast trends of key product/business metrics and make recommendations to improve them. Lead the design, analysis, and interpretation of product experiments.
- Perform data exploration to understand user behavior and identify opportunities for improving and growing Education products. Identify critical business and product functionalities and assess their business impact.
- Develop analysis, forecasting and human/auto evaluations to improve the quality of Google's AI/LLM products, such as Gemini/NotebookLM use-cases for teachers and students, and live experiments.
- Apply technical expertise with observational data analysis, modeling, and causal inference to answer the most important product/business questions.
- Partner with product, engineering, UX and cross-functional teams to influence, prioritize and support product and business strategy. Deliver effective presentations of data-driven insights and recommendations to stakeholders.
