Jobs / United States / General Motors Company
Senior Data Scientist - Product Safety Data Analytics (GPSSC)
General Motors Company · 🇺🇸 Warren, Michigan, United States of America
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 606 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 267 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What General Motors Company paid sponsored hires in similar roles13 certified filings for “Senior Product Manager” (Robotics Engineers) in MI: $142k–$165k, median $155k. Most were filed at wage level IV (62%) — 4 lottery entries, ≈61% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Last confirmed live 3 days agoWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
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Sponsor Radar — General Motors Company
The US Department of Labor certified 606 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 267 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for General Motors Company →
About the role
Job Description The Role The Product Safety Data Analytics team is seeking highly motivated and qualified candidates for the position of Data Scientist focused on hazard monitoring. This is a great opportunity for an innovative data scientist/statistician with strong hands-on experience in statistical analysis, data interpretation, automation, and development of scalable analytical solutions. This role requires strong programming skills and deep knowledge of statistical techniques to solve complex problems, automate analytical workflows, support safety investigations, and strengthen hazard monitoring capabilities. You will be part of a highly collaborative team that values growth, creativity, and a relentless focus on data-driven business transformation. In this role, you will develop and improve analytical solutions to identify, monitor, and analyze potential emerging vehicle safety issues. You will work closely with business partners to understand their challenges and needs, perform appropriate statistical analyses, improve monitoring methods, automate workflows, and provide technical guidance and mentorship across the team. What You’ll Do (Responsibilities): • Develop and help standardize best practices for continuous monitoring of emerging safety issues for use in safety hazard monitoring • Strengthen data-analytics support for safety investigations through improved methods, automated tools, and feedback loops for process improvement • Perform appropriate statistical analyses to deliver sound, unbiased, and actionable results • Analyze signals, patterns, and trends in large and complex data sets to support early identification of potential safety issues • Apply methods such as time series analysis, categorical data analysis, sampling, and multivariate analysis to support investigations and decision-making • Support anomaly detection, diagnostics, prognostics, and root cause analysis for safety-related topics • Identify, design, and implement automation opportunities using a combination of custom software development and off-the-shelf solutions • Develop scalable automated analytical tools, data workflows, and monitoring approaches that improve execution efficiency and consistency • Communicate findings clearly and tell a concise, data-driven story to a wide range of stakeholders, from analyst to senior leadership • Apply strong business acumen and technical judgment to expand and strengthen hazard-monitoring analytics support • Work independently on complex assignments while collaborating effectively across functions • Serve as a resource and mentor for less experienced team members Your Skills & Abilities (Required Qualifications): • B.S. in a quantitative discipline such as Statistics, Mathematics, Econometrics, Operations Research, or another relevant degree • 5+ years of work experience in applied statistics, analytics, engineering, data science, or a related field • Strong background in statistical data analysis such as time series, categorical data analysis, multivariate analysis, and sampling design • Strong background in anomaly detection, diagnostics and prognostics, and root cause analysis • Demonstrated experience in large-scale data analytics • Strong programming capability in Python, SQL, and related analytical tools • Experience working with modern data environments such as Databricks, data pipelines, data preprocessing workflows, and automation of recurring analytical processes • Ability to communicate results and methodologies effectively, including presentation to senior leadership • Strong work ethic, drive for results, and ability to work effectively in an ambiguous environment • Understanding of vehicle safety technologies including design intent, function, and intended field perf