Staff Data Scientist Product, Google Play Games

Minimum qualifications:

• Master's degree in Statistics, Economics, Engineering, Mathematics, a related quantitative field, or equivalent practical experience.
• 7 years of experience with statistical data analysis, modeling, experimentation, causal inference, data mining, querying, and managing analytical projects with programming in SQL, Python, or R.
• 7 years of experience developing and managing metrics or evaluating programs/products.
• 5 years of experience as a people manager within a technical leadership role.

Preferred qualifications:

• Experience managing a team of Data Scientists.
• Experience working with large and multiple datasets/data warehouses, and ability to pull from such data sets using relevant tools and coding.
• Strong business acumen and experience with utilizing unstructured data to answer open-ended business questions.
• Ability to start and direct work in an unstructured environment and comfortable dealing with ambiguity.
• Expertise in experimental design (e.g., A/B, multivariate, Bayesian methods) and incrementality analysis.

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.

• Design and implement automated and standardized analysis tools (e.g. dashboards), empowering business stakeholders to uncover business opportunities and make informed decisions.
• Scrutinize and validate data integrity throughout the collection process, performing data profiling to identify and comprehend data anomalies.
• Investigate the root causes of business problems, providing solutions that go beyond superficial observations.
• Deliver effective presentations of findings and recommendations to multiple levels of leadership, creating visual displays of quantitative information.
• Engage and influence senior stakeholders and cross-functional partners, obtain buy in for potential solutions, adapt messaging and suggested recommendations.