Senior Staff Data Scientist, Product
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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, and managing analytical projects.
- 5 years of experience with data mining, querying (e.g., SQL), developing and managing metrics, and evaluating programs/products.
- Experience with data engineering, investing in data architectures, and building experimentation platforms.
Preferred qualifications:
- 15 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).
- Experience in operating in a complex, cross-functional organization in collaboration with other teams.
- Experience in machine learning techniques, including large language models and AI.
- Experience in solving unstructured business problems with data science and translating results into impactful business recommendations.
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
- Collaborate with a team of analysts working on Google’s applied Machine Learning (ML) problems, and collaborate across engineering teams and functions to drive multiple strategic efforts for which data management and insights is at its core.
- Interact cross-functionally, be a thought partner and influence across ML, architecture, and engineering teams.
- Lead initiatives to improve our data, tools and methodology, beyond the scope of a single product application, to help scale the team's work.
- Apply technical expertise with observational data analysis, modeling or causal inference to answer important product questions.
- Serve as a subject matter expert driving problem definition, metrics development, data extraction and manipulation, visualization, creation, implementation of statistical models, and presenting to stakeholders on key results.
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