Senior Staff Data Scientist, Workspace AI Foundations
Sunnyvale, CA, USA · Staff+
Stay score
odds of building a lasting career here
Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.
Lottery odds assume a STEM candidate.
Personalize to your clock →H-1B wage level
the lottery is wage-weighted — each level is one more entry
$15,757 more — $255,757 — moves this role to Level IV and 4 lottery entries. That figure is inside the range the employer already advertised.
Based on the DOL prevailing wage for this occupation and worksite, a base salary of $255,757 would place this position at wage Level IV. That figure is within the posted range, and I'd like to target it. This role classifies under "Data Scientists" for prevailing-wage purposes.
DOL prevailing wage, 2026-27 wage year · Data Scientists (15-2051) · San Jose-Sunnyvale-Santa Clara, CA. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.
Employer immigration record
from this employer's Department of Labor filings
Files H-1B transfers
Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.
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About the role
- - Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
- - 13 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) (or 10 years work experience and a Master's degree).
Responsibilities
- Lead horizontal metric and evaluation frameworks that quantify engagement, productivity gains, and end-to-end system quality across GenAI models, agentic tooling, context grounding, and safety.
- Deliver clear, executive-ready insights and recommendations that guide product roadmaps, organizational transitions, and resource allocation.
- Define upstream logging and telemetry standards, design scalable data models and ETL pipelines, and build unified semantic layers and self-serve analytics that connect data across Workspace domains.
- Drive experimentation, observational causal inference, and rigorous model evaluations-leveraging AI models/tools as well as human and automated rating systems.
Requirements
- Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
- 13 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) (or 10 years work experience and a Master's degree).
Nice to have
- Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
- 12 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).
- Work on challenges across behavioral, telemetry, and evaluation datasets to identify user adoption, quality or reliability gaps, latency/cost trade-offs, and new methodologies to improve performance.
Skills
- Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
Compensation
- US: $240000 - $333000 (USD) + 25% bonus target + equity + benefits
This listing is sourced directly from Google's careers page and normalized into a canonical job model.