{"id":1593269,"url":"https://alion.io/job/google-staff-data-scientist-measurement-methodology-innovation","title":"Staff Data Scientist, Measurement Methodology Innovation","company":{"id":82,"name":"Google","domain":"google.com","url":"https://alion.io/company/google","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":{"grade":"B","score":75,"open_postings":108,"ghost_share":0,"stale_share":0.981,"repost_share":0,"time_to_fill_p50_days":30,"computed_at":"2026-10-19T05:45:15Z"}},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":158000,"max_usd":315000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":414},"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"LLM","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Machine Learning","optional":true}],"status":"live","first_seen_at":"2026-10-01T09:43:08Z","employer_posted_date":"2026-10-01","last_verified_at":"2026-10-20T03:04:35Z","board_verified":true,"closed_at":null,"days_open":18,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":18},"description":"About the job\nAs a Data Scientist for Search Quality, you will drive measurement technology innovation at the core of the Search Quality. You will spearhead the development of an automated eval platform designed for next-generation experimentation. In this role, you will pioneer novel synthetic modeling techniques that translate multifaceted real-world behavioral and cognitive signals into high-fidelity simulations. You will build a cutting-edge Large Language Model (LLM)-based framework and predictive scoring engines to model complex user dynamics at scale. Furthermore, you will establish advanced validation and backtest simulation frameworks against large-scale historical benchmarks to dramatically accelerate the frontier of product quality evaluation.\nIn Google Search, we're reimagining what it means to search for information - any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally. \nIndividual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits\nLearn more about benefits at Google.\nResponsibilities\nPioneer novel generative modeling and simulation techniques, translating multimodal data and behavioral signals into high-fidelity synthetic evaluation frameworks.\nArchitect and iterate on next-generation LLM-based pipelines, building scalable predictive engines to model complex cognitive dynamics, sentiment, and latent user behaviors.\nDesign and execute rigorous validation paradigms, establishing backtesting frameworks against historical benchmarks to verify simulation fidelity and predictive precision.\nDrive cross-functional innovation with engineering, research, and product teams to integrate automated evaluation platforms into the core experimentation lifecycle.\nConduct advanced analytical and statistical investigations on large-scale discovery environments, developing new methodologies to accelerate product quality measurement and algorithmic iteration.\nQualifications\nMinimum qualifications:\nMaster's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.\n8 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree.\nPreferred qualifications:\n10 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 8 years of work experience with a PhD degree.\nExperience articulating business questions and using mathematical techniques to arrive at an answer using available data. 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