Product Data Scientist, Sellside Ads

About the job

We are a team of product analysts and data scientists who partner within and across Ads product area groups (PAGs) on complex, data-intensive problems. We provide product analytics, in depth analyses, modeling, dashboards, metrics definitions and analytics consulting. We work closely with product managers and engineers to shape the strategy of this business.

Google Ads is at the forefront of AI innovation, applying cutting-edge machine learning and Generative AI models like Gemini to power a multi-billion dollar global business.

Our work directly impacts billions of users by protecting users from harm, improving ad quality, and optimizing campaigns for advertiser return-on-investment. We foster a culture of deep collaboration, partnering closely with teams like Google Research and DeepMind to solve complex challenges. Join us to work on state-of-the-art AI, take on problems at an unparalleled scale, and build the next generation of advertising technology.

US: $138000 - $197000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Make decisions from data, and be capable of maximizing impact by prioritizing requests from different stakeholders.
• Collaborate as part of a team of analysts supporting PMs and engineering teams for our sellside products: AdSense and Google Ad Manager and AdMob.
• Work cross-functionally with analyst colleagues in Finance and Publisher Intelligence.
• Conduct ad-hoc deep dives into experiments and product performance to help prioritize product resource investments. Provide intelligence and quantitative support around auction fundamentals and engaged market dynamics; support our responses to regulatory inquiries and published research into these topics.
• Analyze, uncover, and communicate upcoming risks and opportunities to the business. Develop infrastructure to scale and support existing analyses, and present findings to decision-makers and executives across the company.

Qualifications

Minimum qualifications:

• Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
• 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 of experience with a Master's degree.

Preferred qualifications:

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