Data Scientist Manager, Product, Photos and G1
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Minimum qualifications:
- Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
- 10 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL), or 8 years of experience with a Master's degree.
- 3 years of experience as a people manager within a technical leadership role.
Preferred qualifications:
- Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
- 12 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).
- 4 years of experience as a people manager within a technical leadership role.
- Ability to identify business problems and come up with solutions to solve the problem.
- Ability to lead and grow a team of data scientists through both technical leadership and people management skills.
- Excellent problem-solving, analysis skills and business judgment.
About the job
To empower Photos+G1's organizational mission, our team made up of Data Engineering, Data Science, and Product Operations/Strategy all work closely together towards the mission to understand our users to drive product change. The close collaboration between our complementary technical and strategic skills is our reason for success and allows us to set and accomplish an exciting agenda spanning analytical tools, insights, and product strategies.
Google Photos is a photo sharing and storage service developed by Google. Photos is one of the most sought after products at Google and is looking for both client-side (web and mobile), with server-side (search, storage, serving) and machine intelligence (learning, computer vision) Software Engineers. We are dedicated to making Google experiences centered around the user.
Responsibilities
- Partner closely with Finance, UX, Product Management, and Engineering teams to deliver analytics/experimentation infrastructure and processes that empower the team to deliver insights and decision-making at scale.
- Identify vague business problems where a data science approach is appropriate. Bring structure to the problem, apply the right problem-solving solutions, and recommend actions that improve our product and user experience.
- Lead and grow a team that delivers quality work with a large impact. Create a team foundation with high morale and grow our future data science leaders.
- Foster a culture of continuous learning. Proactively identify new data sources, tools, and methodologies to enhance our problem-solving capabilities and drive innovation.
- Serve as a key conduit of understanding the relationship between teams, and elucidate and quantify tradeoffs between competing goals.
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