Business Data Scientist, Google Customer Solutions

Job description

In most instances, this position requires in-person interviews as part of the hiring process.
Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; New York, NY, USA; San Francisco, CA, USA . Minimum qualifications:
• Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
• 3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
Preferred qualifications:
• 4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
About the job
The Google Customer Solutions (GCS) Data Science team is working on challenging yet interesting problems for Google Global Business Organization (GBO). Our vision is to build efficient and scalable ML models that help small and midsize businesses around the world to grow their business leveraging the power of Google solutions.
We look for candidates who are passionate about solving real-world problems with the latest research in applied deep learning, causal inference and measurement theory. We work with product teams to understand their objectives, business requirements and constraints, and key metrics. We propose, build, evaluate and debug machine learning models and algorithms; we integrate our pipelines, models and predictions into production serving systems.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $138000 - $197000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google .
Responsibilities
• Design, develop, and validate robust causal inference models (e.g., synthetic control, difference-in-differences, double machine learning) to isolate the incremental impact of GCS programs.
• Partner with business teams to design and execute rigorous A/B tests, defining the sample sizes, power analyses, and success metrics required for valid results.
• Stay current with the latest academic research in causal ML and econometrics, proactively prototyping new methods to improve the precision of our impact estimates.
• Distill highly technical methodologies and black box model outputs into clear, prescriptive business narratives for non-technical executive audiences.
• Establish comprehensive monitoring systems to track model performance, detect data drift, and ensure the ongoing accuracy of deployed measurement frameworks.
Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .