Senior Data Scientist, Ads Metrics

Requirements:

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

Nice to haves:

• Master's degree or PhD in a quantitative discipline (e.g., Statistics, Operations Research, Bioinformatics, Economics, Computational Biology, Computer Science, Mathematics, Physics, or Engineering).
• 8 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree.
• Experience with regression analysis, experiment design, sampling methods, causal inference, time-series analysis, and hierarchical models.
• Experience in data analysis to solve business problems in complex business environments.
• Excellent scientific writing, communication, and presentation skills.

What you'll be doing:

• Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions to answer. Provide feedback to translate and refine business questions into analysis, evaluation metrics, or mathematical models.
• Use custom data infrastructure or existing data models as appropriate, using knowledge. Design and evaluate models to mathematically express and solve defined problems.
• Gather information, business goals, priorities, and organizational context around the questions to answer, as well as the existing and upcoming data infrastructure.
• Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Format, re-structure, or validate data to ensure quality, and review the dataset to ensure it is ready for analysis.

Perks and benefits:

• Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google's Applicant and Candidate Privacy Policy.
• Equal opportunity and affirmative action employer commitment, promoting diversity and inclusion.
• Accommodations available upon request via the Accommodations for Applicants form.
• Global collaboration requiring English proficiency for all roles unless stated otherwise in job postings.
• Google does not accept agency resumes and is not responsible for fees related to unsolicited resumes.