Senior Data Scientist, Product, Google Store

Minimum qualifications:

• Master's degree in Statistics, Economics, Engineering, Mathematics, a related quantitative field, or equivalent practical experience.
• 5 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL)

Preferred qualifications:

• 8 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).
• Experience with experimental design (e.g., A/B, multivariate, Bayesian methods) and incremental analysis.

5 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) 5 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) 5 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL)

About the job

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.

Responsibilities

• Provide investigative thought leadership through proactive and strategic contributions; consistently use insights and analytics to drive decisions and alignment throughout the organization.
• Develop the investigative roadmap that delivers against the broader strategy. Establish the project goals, coordinate resources, and provide technical leadership in-line with the long-term objectives.
• Define and report Key Performance Indicators (KPIs) and impact as part of regular business reviews with the cross-functional and cross-organizational leadership team. Translate analysis results to business insights or product improvement opportunities.
• Perform analysis utilizing tools (e.g., SQL, R, Python). Help solve problems, narrowing down multiple options into the best approach, and take ownership of open-ended ambiguous business problems to reach an optimal solution.