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.

Google Ads is helping power the open internet with the best technology that connects and creates value for people, publishers, advertisers, and Google. We’re made up of multiple teams, building Google’s Advertising products including search, display, shopping, travel and video advertising, as well as analytics. Our teams create trusted experiences between people and businesses with useful ads. We help grow businesses of all sizes from small businesses, to large brands, to YouTube creators, with effective advertiser tools that deliver measurable results. We also enable Google to engage with customers at scale.

Responsibilities

• Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Format, re-structure, and validate data to ensure quality.
  
• Run business-critical ad-hoc product analyses with fast turnaround and present results to executive stakeholders to deliver insights and support product decisions in Search Ads.
• Collaborate with Product Managers, Engineers, and other Data Scientists to identify and clarify business or product questions, and translate them into tractable analyses and metrics.
• Develop and maintain product health metrics and dashboards to track key performance indicators, identify trends, and provide insights. Ensure data quality and consistency to empower other teams in delivering insights.
• Identify and size opportunities for product growth and improvement, such as increasing adoption, reducing churn, or improving performance, and collaborate with cross-functional teams to implement solutions.