Data Scientist Product, Analytics, Insights and Measurement

Key Skills

Data science techniques, Product Analytics, Python Programming, R Programming, SQL

Job Description

Minimum qualifications:

• Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
• 5 years of work experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems), and coding (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.
• Experience with privacy-preserving technologies and data regulations.
• Understanding of digital advertising measurement concepts, including attribution modeling, incrementality testing, and media mix modeling (MMM).

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

• Driving business growth and help the team to empower advertisers with the tools and insights they need to navigate the evolving digital advertising landscape.
• Develop quantitative models and frameworks to assess the business opportunity associated with improvements in attribution, incrementality testing, full-funnel measurement, and online-to-offline (O2O) measurement.
• Quantify the impact of data deprecation and regulatory changes on Ads performance. Develop metrics to track the effectiveness of the mitigation strategies and data durability initiatives.
• Define success metrics for the efforts to create a unified measurement platform. Analyze the impact of closing measurement gaps and enhance the customer value proposition.