Role overview
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.
What you'll work on
- 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).
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.
What we're looking for
- 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.