Data Scientist, Product, Google Photos
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Minimum qualifications:
- Master's degree in Statistics, Economics, Engineering, Mathematics, a related quantitative field, or equivalent practical experience.
- 5 years of experience with statistical data analysis, data mining, and querying (e.g., SQL).
Preferred qualifications:
- Experience with experimental design (e.g., A/B, multivariate, Bayesian methods) and incremental analysis.
- Experience with utilizing unstructured data to answer open-ended business questions.
- Experience working with multiple datasets/data warehouses and ability to pull from data sets using tools and coding.
- Knowledge of advanced query optimization techniques.
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.
As a Product Data Scientist, you will be part of a team that drives business outcomes for ads customers through automation and platforms, encouraging long-term investments with Google.
Responsibilities
- Partner closely with Product Management and Engineering to deliver robust analytics/experimentation infrastructure and processes that deliver insights and decision-making at scale for Google One and its cross-Product Area partners.
- Partner closely with the ML team to deliver insights that accelerate our ML-driven targeting and growth engine capabilities.
- Identify vague and complex business problems and come up with analytical solutions that improve our product and user experience.
- Perform analysis utilizing relevant 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.
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