Skills this job asks for
ComplianceSQLPython
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Sponsorship verdict
Sponsorship possible
One solid signal, not two. Worth applying, and worth asking about sponsorship early.
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✓
Employer is on a government sponsor recordThe US Department of Labor certified 39 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.
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The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
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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.
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✓
What Glaxosmithkline LLC paid sponsored hires in similar roles3 certified filings for “AIR & Vaccine Medical Insight Analyst” (Data Scientists) in NC: $107k–$127k, median $127k.
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✓
Confirmed live todayWhen a source last listed this job as open.
Details and sources
- Employer is on a government sponsor record
- The US Department of Labor certified 39 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. Source: LCA disclosure data (US Department of Labor (OFLC)).
- No salary bar for this route
- H-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 Glaxosmithkline LLC paid sponsored hires in similar roles
- 3 certified filings for “AIR & Vaccine Medical Insight Analyst” (Data Scientists) in NC: $107k–$127k, median $127k. Most were filed at wage level IV (67%) — 4 lottery entries, ≈61% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
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.
About the role
Business Introduction
At GSK, we have bold ambitions for patients, aiming to positively impact the health of 2.5 billion people by the end of the decade. Our R&D focuses on discovering and delivering vaccines and medicines, combining our understanding of the immune system with cutting-edge technology to transform people’s lives. GSK fosters a culture ambitious for patients, accountable for impact, and committed to doing the right thing, making sure that we focus our efforts on accelerating significant assets that meet patients’ needs and have the highest probability of success. We’re uniting science, technology, and talent to get ahead of disease together.
Find out more:
Our approach to R&D
Position Summary
Join us as a Data Information Model Developer and help turn complex biomedical data into models that scientists and AI agents can use with confidence. You will design disease data information models for priority discovery areas, write the mapping rules that bring harmonized data them, and build the quality checks that keep them trustworthy. This is a hands-on role: you will work in code and modelling tools every day, use AI assistants to work faster, and partner with research, ontology and data platform teams as well as external partners. We value curiosity, attention to detail, and a positive mindset. This role offers you the chance to grow your skills while making a meaningful impact aligned with GSK’s mission to unite science, technology, and talent to get ahead of disease together.
Responsibilities :
This role will provide YOU the opportunity to lead key activities to progress YOUR career. These responsibilities include some of the following:
- Design, develop, and main tain data information models and frameworks that support research and innovation.
- Work closely with cross-functional teams to understand their data needs and translate them into clear, reusable data structures.
- Document data definitions, relationships, and lineage to ensure clarity and usability for people as well as enabling context for AI agents to interpret the data correctly.
- Implement processes to ensure data quality, consistency, and compliance .
- Collaborate with engineering teams to integrate models into data platforms and pipelines.
- Support continuous improvement by reviewing and refining data modelling practices.
- Work with research scientists, data stewards and data platform teams to agree models and get them adopted.
Why You?
Basic Qualification
We are seeking professionals with the following required skills and qualifications to help us achieve our goals:
- Degree in Computer Science, Data Science, Information Management, or a related field.
- Proven experience in data modelling, designing information architectures, or similar roles in pharma setting.
- Proven experience curating, harmonizing or integrating biomedical, pharmaceutical or healthcare data.
- Proven experience using AI assistants or generative AI tools in daily work, with a critical eye on their output.
- Strong skills in data analysis and the ability to translate complex requirements into clear models.
- Familiarity with database technologies and data integration concepts.
- Ability to write clear documentation and communicate with technical and non-technical colleagues.
- Working knowledge of biomedical ontologies and standards such as NClt, MONDO, EFO, GO, ChEBI, CDISC
Preferred Qualification
If you have the following characteristics, it would be a plus:
- Understanding of data governance, privacy, and security best practices.
- Familiarity with programming or scripting languages like SQL, Python, or others used in data workflows.
- Experience preparing data for AI agents.
- Contributions to standards or ontology communities (e.g. CDISC, FHIR, OBO Fo
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