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# Business Data Scientist, Applied Machine Learning, GCS

- **Company:** Google LLC
- **Location:** Mountain View, CA, United States
- **Experience:** Experienced
- **Salary:** $138,000.0 - $198,000.0
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Databases, R (Programming Language), Monitoring of Systems, Python (Programming Language), Machine Learning, SQL Databases, Information Technology
- **Published:** July 15, 2026
- **Apply:** https://dejobs.org/x/x/19D2927D676E4C1E81F0339904194C25/job/

## About the Role

Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area., * 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., * PhD in a quantitative discipline such as Computer Science, Engineering, Economics, Statistics, Mathematics, Physics, Neuroscience, or equivalent practical experience.
 * 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.
 * Experience in driving a project from an experimental idea to a proof-of-concept to a launched product feature.
 * Experience in publications and working with technologies.

## Description

* 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 A/B tests, defining the sample sizes, power analyses, and success metrics required for valid results.
 * Track the latest academic research in Causal ML and Econometrics, proactively prototyping new methods to improve the precision of impact estimates.
 * Translate highly technical methodologies 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.


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