Data Scientist III, Product, Operations Data Science

Minimum qualifications:

• Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, a related quantitative field, or equivalent practical experience.
• 3 years of experience with statistical data analysis, data mining, and querying (e.g., SQL).
• 1 year of experience managing analytical projects.

Preferred qualifications:

• 5 years of work experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems), and coding (Python, R, SQL).
• 4 years of experience as a data scientist, including applying advanced analytics to planning and infrastructure problems.
• Experience in energy and climate domain, or greenhouse gas accounting.

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.

Operations Data Science (ODS) is a team of Data Science and Business Analysis experts, who provide model-based decision support to scale Google's Technical Infrastructure optimally.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

• Perform analysis by utilizing relevant tools (e.g., SQL, R, Python). Using comprehensive technical knowledge, use custom data infrastructure or existing data models.
  
• Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Format, re-structure, and validate data to ensure quality.
• Report Key Performance Indicators (KPIs) to support business reviews with a cross-functional/organizational leadership team. Translate analysis results to business insights or product improvement opportunities.
• Provide analytical insights and recommendations to influence product feature development decisions, and with some guidance.
• Build and prototype analysis and business cases iteratively to provide insights at scale. Develop comprehensive knowledge of Google data structures and metrics.