Product Data Scientist, Pixel

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By applying to this position you will have an opportunity to share your preferred working location from the following:
Mountain View, CA, USA;
Chicago, IL, USA
.

• Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
• 5 years of work experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems), and coding (Python, R, SQL) (or 2 years work experience and a Master's degree).
• Experience analyzing device telemetry to triage issues; distinguishing between software regressions and hardware limitations (i.e., power, performance, connectivity, or stability domains).

• Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
• Experience analyzing time-series data or telemetry from hardware devices.
• Experience working on Android or other embedded systems.

As a Data Scientist on the Pixel team, you will work with key Pixel phone-related stakeholders including hardware and software engineering, product management, safety, reliability, and customer support: to understand their business-related questions, identify reasonable ways to answer them using data, and provide meaningful recommendations on strategy. You will construct and use high information density visualizations and build appropriate statistical models to help identify the key variables that impact Pixel users’ experience the most.

You will also build data pipelines when needed to automate the model fitting and export the model output for further use such as dashboarding.

As a Product Analyst for Pixel, you will drive data-driven improvements for Google's consumer hardware. You will play a key role in the Real Time Negative Sentiment (RTNS) project, analyzing complex telemetry to identify root causes of user frustration like severe performance degradation, connectivity problems, or application stability. Leveraging your background in embedded systems or systems engineering, you will triage issues across power, performance, connectivity, and stability domains.

You will translate high-level signals into technical insights—identifying kernel wakelocks, memory thrashing, or bus failures—and build statistical models to attribute these events to specific system health indicators. Collaborating with hardware and software engineers, you will transform large-scale product health datasets into actionable strategies that enhance the reliability and quality of Pixel devices.

The Google Pixel team focuses on designing and delivering the world's most helpful mobile experience. The team works on shaping the future of Pixel devices and services through some of the most advanced designs, techniques, products, and experiences in consumer electronics. This includes bringing together the best of Google’s artificial intelligence, software, and hardware to build global smartphones and create transformative experiences for users across the world.

The US base salary range for this full-time position is $132,000-$189,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

• Perform analysis by utilizing relevant tools (e.g., SQL, R, Python). Use custom data infrastructure or existing data models.
• Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Format, re-structure, and validate data to ensure quality.
• Report Key Performance Indicators (KPIs) to support business reviews with cross-functional/organizational leadership teams. Translate analysis…