Jobs / United States / General Motors Company
Staff Data Scientist
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 roles3 certified filings for “Software Development” (Data Scientists) in MI: $130k–$249k, median $168k. Most were filed at wage level IV (100%) — 4 lottery entries, ≈61% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen 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).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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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 This role is categorized as hybrid. This means the successful candidate is expected to report to Warren Global Technical Center three times per week, at minimum [or other frequency dictated by the business if more than 3 days]. The Role This is a unique opportunity to become part of a diverse team comprising advanced analytics professionals. Together, we spearhead the discovery of opportunities and craft solutions, advancing analytics initiatives across our global operations. This role applies leading analytic practices and methods, designs and leads iterative development and learning cycles, and ultimately produces new and creative analytic solutions that become part of the operating fabric of the global enterprise. What You'll Do • Developing industry leading analytics solutions including: • Assessing existing analytic models and architectures, reviewing for gaps against business needs and industry best practices • Identifying detailed data needs, sources, and structure to support solution development • Determining the analytic approaches to be used and defining and applying the appropriate methodologies • Employing Proof-of-Concepts for exploratory and targeted data analyses, leading to breakthrough solutions • Ensuring integrity of the analytical solutions in terms of the underlying statistical and economic models and assumptions • Designing and developing project-specific models. • Architecting analytical tools to productionize cloud-based analytical models • Monitoring and sustaining model effectiveness Your Skills & Abilities (Required Qualifications) • 10+ years of experience in statistics, econometrics, forecasting, advanced analytics, or related quantitative fields • Bachelor’s degree AND Ph.D. required in a technical discipline, such as statistics, mathematics, computer science, economics, operations research, or a related quantitative field • Deep expertise in statistics, econometrics, forecasting, and predictive modeling • Strong command of model development, model validation, uncertainty quantification, and performance monitoring • Demonstrated ability to connect methodological choices to business decisions, operational constraints, and end-user impact • Advanced programming skills for analytical model development, data pipelines, and reproducible workflows • Strong data fluency across structured, time-series, and panel-style analytical data • Significant experience building or overseeing forecasting approaches used for planning, scenario evaluation, or business decision-making • Ability to translate economic, operational, or market signals into robust forecasting frameworks • Experience balancing statistical rigor with practical constraints, data limitations, and stakeholder timelines • Strong judgment in model comparison, feature selection, assumption management, and interpretation of results • Ability to understand complex business processes, and how business value is created. Based on that knowledge, propose analytic strategies and solutions that challenge and expand the thinking of the working team. • Ability to create structured problem statements and conceptualize potential solutions from rough client specifications and information. • Ability to communicate analyses, status, results, and recommendations to business management and executives in business terms. What Can Give You a Competitive Advantage (Preferred Qualifications) • Automotive experience • Recognized subject matter expertise with a track record of leading large, visible, cross-functional analytical efforts • Strong listening and communications skills, with ability to clearly and concisely explain complex problems and technologies to non-expert and executive audiences. • Highly collaborative work style,