Product Data Scientist, Enterprise Buying Platforms

Minimum qualifications:

• Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
  
• 2 years of work experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems), and coding (Python, R, SQL) (or 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.
• 3 years of work experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems), and coding (Python, R, SQL).
• Understanding of digital advertising measurement concepts, including attribution modeling, incrementality testing, and media mix modeling (MMM).
• Excellent communication and presentation skills with the ability to influence stakeholders.
  
  

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.

• Execute defined, moderately difficult investigative tasks under guidance from the manager or executive team member/TL. Execute end-to-end analysis with minimal guidance.
• Manage workload to reflect the priorities set by the team, work towards a timeline, and communicate slippage. Handle data communication, limits, and importance.
• Collaborate with Product Managers, Engineers, and Research Scientists to define and track key performance indicators (KPIs) for Google Ads measurement products. Select appropriate approaches from clear options to address technical challenges under guidance from managers or executive team members. 
• Conduct in-depth analysis of large datasets to identify trends, patterns, and insights that inform product strategy and development.
• Communicate data and analysis in a clear and concise manner to various stakeholders, including product leadership, engineering teams, and business partners.