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Senior Data Scientist, Ads Metrics

Senior Data Scientist, Ads Metrics

2 Weeks ago • 3-8 Years • Data Analyst

About the job

Summary

As a Senior Data Scientist, Ads Metrics at Google, you'll collaborate with engineers, product managers, researchers, and analysts to innovate and enhance experiment design, causal inference, and time-series analysis for critical product launches. Responsibilities include clarifying business questions, designing and evaluating mathematical models, gathering and validating data (using SQL, R, Python), and ensuring data quality. You will translate business needs into analytical solutions, utilizing custom or existing data infrastructure. The role demands expertise in statistical data analysis, regression analysis, and potentially causal inference, time-series analysis, and hierarchical models. This position requires strong communication and presentation skills.

6 skills required for this role

Test your skills to join the top 1% applicants for this job

unity

python

sql

data-science

forecasting-budgeting

presentation-skills

Must have:

Master's degree in quantitative field or equivalent experience
5+ years experience in analytics/data science
Experience with statistical data analysis and experimental design
Proficiency in Python, R, SQL
Regression analysis for prediction and forecasting

Good to have:

PhD in a quantitative discipline
Experience with causal inference, time-series analysis, hierarchical models
8+ years of relevant work experience
Excellent communication and presentation skills

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Minimum qualifications:

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.

Preferred qualifications:

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.

About the job

In this role, you will collaborate with software engineers, product managers, researchers, and analysts to to innovate and enhance experiment design, causal inference, and time-series analysis for business-critical launches.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

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). Independently format, re-structure, or validate data to ensure quality, and review the dataset to ensure it is ready for analysis.

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About The Company

Google

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A problem isn't truly solved until it's solved for all. Googlers build products that help create opportunities for everyone, whether down the street or across the globe. Bring your insight, imagination and a healthy disregard for the impossible. Bring everything that makes you unique. Together, we can build for everyone.