Product Data Scientist, Pixel

Google • Mountain View, CA

5h

About The Position

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.

Requirements

• 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).

Nice To Haves

• 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.

Responsibilities

• 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 results to business insights or product improvement opportunities.
• Work closely with embedded systems engineers to translate high-level negative sentiment signals into actionable technical insights (e.g., identifying specific kernel wakelocks, memory thrashing, or bus failures).
• Conduct advanced data analysis (including visualization and statistical modeling) to make business recommendations. Focus on why users reboot their phones (what is frustrating and how to quantify impact).

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level