Data Scientist, Chrome

Google Google · Big Tech · Munich, Germany

Data Scientist for Chrome responsible for defining success metrics, designing testing environments, and launching intelligent features that enhance user experience by anticipating user intent and streamlining tasks. The role involves leveraging advanced statistical and machine learning techniques to pioneer behavioral insights and experimentation frameworks for AI capabilities and agentic experiences.

What you'd actually do

  1. Leverage advanced statistical methods on massive, complex datasets to extract insights from billions of events and thousands of features across organizational sources.
  2. Analyze intricate AI product and platform usage patterns, translating data-driven insights into actionable product strategy and engineering decisions.
  3. Works cross-functionally with Research, Engineering, and Product teams (e.g., Google DeepMind, Search, Shopping) to translate ambiguous data challenges into strategic business opportunities.
  4. Make clear, concise product and engineering recommendations to drive major impact.
  5. Interest and aptitude in data, metrics, analysis and trends and applied knowledge of measurement, statistics and program evaluation.

Skills

Required

  • Bachelor's degree in Statistics, Economics, Engineering, Mathematics, a related quantitative field, or equivalent practical experience.
  • 5 years of experience with statistical data analysis, data mining, and querying (e.g., SQL).
  • 2 years of experience managing investigative projects.

Nice to have

  • Master's degree in Statistics, Economics, Engineering, Mathematics, a related quantitative field.
  • 3 years of experience in scripting, statistical analysis (e.g., R, Stata, SPSS, SAS), developing and managing metrics, and evaluating programs/products.
  • 1 year of experience working in a complex, matrixed organization.
  • Experience working and communicating in areas with significant leadership and stakeholder scrutiny.
  • Ability to articulate product questions, pulling data from large datasets (SQL, BigQuery or equivalent technologies), and using statistics to arrive at an answer.
  • Ability to translate analysis results into business recommendations with excellent written and verbal communication, problem-solving and business judgment skills.

What the JD emphasized

  • guardrails
  • success metrics
  • rigorous testing environments
  • launch intelligent features

Other signals

  • AI capabilities
  • agentic experiences
  • anticipate user intent
  • streamline daily tasks
  • execute complex actions
  • guardrails
  • success metrics
  • rigorous testing environments
  • launch intelligent features