Research Data Scientist, Ads Insight and Measurement

Minimum qualifications:

• Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field, or equivalent practical experience.
• 3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases, or statistical analysis, or a PhD degree.

Preferred qualifications:

• 5 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases, or statistical analysis, or a PhD degree.
• Experience with optimization techniques.
• Experience with high-dimensional statistics.

About the job:

As a Data Scientist working on Ads Insights and Measurement, you will develop, evaluate and improve the entire range of Google's advertising products including Search, Display, Apps, TV and Video (YouTube). You will collaborate with a multi-disciplinary team of engineers, analysts and product managers to develop new science and to translate it into deployed products at scale. You will also play a key role in developing new ideas and methods that drive ad measurement and business generation, including paradigm-shifting ad-measurement science and products for the privacy-preserving future of digital advertising and will be a key part of building and driving impact on ad-systems both at Google and in the advertising technology and marketing technology industry as a whole, globally.The US base salary range for this full-time position is $147,000-$211,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Responsibilities:

• Design and evaluate custom data infrastructure or existing data models using specialized knowledge to mathematically express and solve defined problems with limited precedent.
• Shape and support new data-driven and privacy-preserving advertising and marketing products in collaboration with engineering, product, and customer-facing teams.
• Define relevant questions about advertising effectiveness, incrementality assessment, the impact of privacy, user behavior, brand building, aiming, and bidding.
• Develop and implement quantitative methods to answer those questions through team collaboration.
• Solve difficult, non-routine analysis problems with data sets, applying problem-solving methods as needed and conducting analyses that include data gathering and requirements specification, exploratory data analysis, model development, and written and verbal delivery of results to business partners and executives.