Data Scientist, Google Photos and Google One, Product

Minimum Qualifications:

• Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field, or equivalent practical experience.
• 5 years of experience with analysis applications (e.g., extracting insights, performing statistical analysis, or solving business problems), and coding (e.g., Python, R, SQL), or 2 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.

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. 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 with Finance, User Experience (UX), Product Management (PM), and Engineering to deliver analytics/experimentation infrastructure and processes that empower the team to deliver insights and decision-making.
• Identify business problems where a data science approach is appropriate. Bring structure to the problem, apply the right investigative solutions, and recommend actions that improve the product and user experience.
• Promote a culture of learning within the team. Identify and advocate new data sources, tools, and methodologies to enhance the investigative capabilities and drive innovation.
• Manage relationships between cross-product area teams, and elucidate and quantify tradeoffs between engaging goals.