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Internet Services, Software, AI, Cloud Computing, Hardware

Staff Product Data Scientist, Google Labs

Mountain View, CAOnsiteFull TimeStaff$192,000–$278,000 /yrPosted 1 month agoVisa sponsorship available

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Required skills

  • analytics
  • statistical analysis
  • Python
  • SQL
  • data gathering
  • requirements specification
  • processing
  • deliverables
  • presentations
  • organization executives

Nice to have

  • statistician
  • data scientist
  • product analyst
  • linear models
  • multivariate analysis
  • causal inference

Role summary

Google Labs is seeking a Staff Product Data Scientist to join their Data Science team. This role involves using analytics to solve product or business problems, performing statistical analysis, and coding in languages like Python, R, and SQL. You will work closely with product teams on growth analysis, quality evaluation, and user insights, developing analytical tools and communicating actionable results to influence product direction. The position requires a strong quantitative background and experience in applying advanced analytical methods to large, complex datasets. The role also involves presenting findings to executives and advocating for data-driven changes.

Minimum qualifications:

  • Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
  • 10 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL), or 8 years work experience with a Master's degree.

Preferred qualifications:

  • Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
  • 12 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).
  • 2 years of work experience (e.g., as a statistician, data scientist, or product analyst), including statistical data analysis such as linear models, multivariate analysis, causal inference, and sampling methods.
  • Experience articulating business questions and using mathematical techniques to arrive at an answer using available data.
  • Experience translating analysis results into business recommendations.

About the job:

Google Labs exists to discover and deliver new products that advance Google’s mission. Labs builds innovative new products and gets them into the hands of users as quickly as possible. The Labs team also runs labs.google, a place where you can try and co-create with Google's latest AI. We co-create with internal and external teams to showcase their bold and responsible ideas, so we can all shape the future of technology together (see go/labs).

For this role, you will be joining the Data Science team within Labs. The Labs Data Science team is a horizontal team, and we help the broader Labs team with metrics, experimentation, evaluation, insights, and data-driven decision making.

The Labs Data Science team is a horizontal team that supports quality evaluation, growth analysis, and data-driven decision making across the portfolio of Labs products. In this role, you will work closely with Labs product teams (Product Managers, Engineers, and cross-functional partners) on selected analysis projects. Example projects include growth and funnel analysis, quality evaluation (autoraters, metrics, eval set development), top-line metrics development, and user insights. You will work with these teams to develop scalable analytical tools (dashboards, metrics, pipelines), and also to communicate actionable results to the product teams to help influence product direction.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $192000 - $278000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities:

  • Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed.
  • Conduct end-to-end analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
  • Share/present analysis to organization executives in order to share insights and influence product direction.
  • Build and prototype analysis pipelines iteratively to provide insights at scale.
  • Develop comprehensive understanding of Google data structures and metrics, advocating for changes where needed for both products development and sales activity.
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