Jobs / United States / Hewlett Packard Enterprise Company
Data Scientist (Houston, Texas)
Hewlett Packard Enterprise Company · 🇺🇸 2 Locations
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 486 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 167 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 Hewlett Packard Enterprise Company paid sponsored hires in similar roles2 certified filings for “Senior Data Scientist” (Data Scientists) in TX: $68k–$133k, median $100k. Most were filed at wage level I (50%) — 1 lottery entry, ≈15% 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 — Hewlett Packard Enterprise Company
The US Department of Labor certified 486 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 167 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 Hewlett Packard Enterprise Company →
About the role
Data Scientist (Houston, Texas) This role has been designed as 'Hybrid' with a requirement that you will work on average 2 days per week from an HPE office. Who We Are: Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE. Job Description: HPE is seeking a Data Scientist work in our Houston, Texas office on a hybrid schedule. The Data Scientist will design, develop and apply programs, methodologies and systems based advanced analytic models (e.g. advanced statistics, operations research, computer science, process) to transform structured and unstructured data into meaningful and actionable information insights that drive decision making. The Data Scientist will use visualization techniques to translate analytic insights into understandable business stories (eg. descriptive, inferential and predictive insights). The Data Scientist will embed analytics into client’s business processes and applications. Combines business acumen and scientific methods to solve business problems. The Data Scientist will contributions include applying developed subject matter expertise to solve common and sometimes complex technical problems and recommending alternatives where necessary. Might act as project lead and provide assistance to lower level professionals. Exercises independent judgment and consults with others to determine best method for accomplishing work and achieving objectives. Location: Hybrid schedule in our Houston, Texas office Responsibilities: • Formulates and defines analytics solution objectives and technical requirements based on user needs, an understanding of business processes, industry requirements, and advanced analytic models (statistical, operations research, computing, process). • Conceptualizes, builds, develops and enhances a client's analytic model. Selects the relevant analytic modeling methodology for the use case, available structured and unstructured data, cost and timing constraints to solve the business issue and deliver clear business focused insights. • Embeds analytic models in an enhanced business process of operational system by collaborating with Application Developers. Responsible for measuring business performance based on the model. • As a fully functioning analytics team member, applies best practices to analytics solutions and contributes to the development of improved best practices. Leads the model enhancements. • Summarizes complex ideas by developing visual models to display insights to simplify user experience. • Communicate the analytics solution to the appropriate stakeholders. Education and Experience Required: • Bachelors Degree in Statistics, Operations Research, Computer Science or equivalent preferred. Or Master´s Degree in these areas is preferred • 2 + years of relevant experience. Knowledge and Skills: • Advanced knowledge of advanced data science methodologies including but not limited to classical regression, neural nets, CHAID, CART, association rules, sequence analysis, cluster analysis, and text mining. • Ability to translate business requirements into mathematical models and data science objectives to achieve mea