Senior Data Scientist, Product, Google Ads

Key Skills

Data science techniques, 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.
• 8 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL), or 5 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 working in an adversarial analytics domain, such as trust and safety, fraud detection, risk management, or cyber-security.

About the job

The Advertiser Platform (AP) team drives better business outcomes for ads customers through automation and critically important platforms, encouraging long-term investments with Google. The AP Product Analytics (APPA) team enables the AP team to make data-driven decisions by building tooling, maintaining datasets, and by measuring and delivering insights for improving key metrics for our scaled and automated Google Ads products.

The US base salary range for this full-time position is $156,000-$229,000 + 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.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Partner with Product Managers, Engineers, and other cross-functional teams to define the product strategy and roadmap for Advertiser Safety, using data-driven insights to identify and prioritize opportunities.
• Define, develop, and steward the key success metrics for the organization, including measures of advertiser friction (e.g., Advertiser Policy Hours) and end-user harm (e.g., policy violating impressions).
• Act as a data advocate within the team, translating complex analytical findings into actionable recommendations and promoting a culture of data-driven decision-making.
• Design, execute, and analyze A/B tests and other experiments to measure the impact of new features and policy changes on advertiser experience, user safety, and business outcomes.

Perform exploratory data analysis and opportunity sizing to uncover new strategies to reduce account takeover incidents, prevent financial losses, and improve the overall efficiency and recall of our safety platforms.