Requirements:

Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, a related quantitative field, or equivalent practical experience.
5 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 3 years of experience with a PhD degree.
Experience with statistical data analysis and experimental design.

Nice to haves:

8 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of experience with a PhD degree.
4 years of experience as a data scientist, including applying advanced analytics to planning and infrastructure problems.
Experience designing and building machine learning models.
Experience with optimization models.
Excellent problem-framing, problem-solving and project management skills.

Develop, maintain, support, and enhance custom forecasting and capacity planning tools for Google Product Area resource planning.
Lead projects with analysis and modeling, drawing from multiple analytical methods to choose the right tool and right level of complexity appropriate for the business challenges.
Engage broadly with the organization to identify, prioritize, frame, and structure complex and ambiguous challenges, where advanced analytics projects or tools can have the biggest impact.
Help define the direction and influence the direction of the associated engineering and infrastructure work.
Articulate business questions and use mathematical techniques to arrive at an answer using data and translate analysis results into business recommendations.