Jobs / United States / Humana INC
Research Scientist 2
Humana INC · 🇺🇸 Remote Nationwide · Remote
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 260 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 130 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 Humana INC paid sponsored hires in similar roles2 certified filings for “Research Scientist 2” (Data Scientists) in IN: $86k–$112k, median $99k. 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 — Humana INC
The US Department of Labor certified 260 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 130 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 Humana INC →
About the role
Become a part of our caring community Humana’s Clinical Innovation and Trend Analytic Team is seeking a Research Scientist 2 (Remote). Healthcare is rapidly changing, and our members are living longer, often with more chronic conditions. The Clinical Innovation and Trend Analytic team identifies opportunities and builds solutions to improve clinical outcomes and lower costs for millions of Medicare Advantage beneficiaries. This is done through an evidence-based approach using data analytics, clinical expertise, strategic mindset, and rigorous study designs. In this multi-disciplinary team, you will have the opportunity to work closely with strategy partners and clinicians to shape Humana’s clinical strategies and initiatives. The Research Scientist 2 applies statistical and epidemiologic principles to identify trends, assess cause-effect relationships, and size potential opportunities using high volumes of complex data. The Research Scientist 2 work assignments are varied and require interpretation of data and independent judgement. Responsibilities As a Research Scientist 2, you will: • Do exploratory analysis on populations, trends, and clinical conditions to inform potential opportunities for trend savings and clinical outcomes improvement for our members. • Collaborate with clinicians and clinical informaticists to define various clinical concepts and extract clinical information from medical, pharmacy, and lab claims for analytics and modeling purposes • Leverage a wide range of analytics methods from descriptive analysis to epidemiological methods • Design outcomes studies and perform program evaluation using randomized controlled trials, propensity matching, difference-in-difference models, or other experimental/quasi-experimental methods. • Conduct literature reviews and intervention research to assess engagement rates and treatment effect sizes of interventions that are in the early stages of design and implementation. • Write code in SQL, SAS, and Python to assemble data, create analytic variables/features, design visuals and charts, and statistical models for research/science use-cases. • Translate analytic results into key takeaways with actionable insights and communicate to business partners • Understand department, segment, and organizational strategy and operating objectives, including their linkages to related areas • Make decisions regarding research methods, occasionally in ambiguous situations with general guidance Use your skills to make an impact Required Qualifications • Master's Degree in a quantitative discipline such as Epidemiology, Biostatistics, Economics, Statistics, Clinical Informatics, Engineering, and/or related fields • 2+ years of experience that includes: • Skills to create datasets and analytical variables from large and complex data environments by writing code in SQL, SAS, and Python. • Applying research methods to transform high volumes of complex data into actionable insights. • Experience with experimental and quasi-experimental methods such as randomized controlled trials, propensity matching, or difference-in-difference models. • Strong interest in healthcare and desire to make a positive impact on health outcomes. • Ability to work collaboratively within a multi-disciplinary team, to deliver quality analytical work, and communicate results and insights clearly to business partners. Preferred Qualifications • Healthcare or managed care working experience • Experience working with medical, pharmacy, and lab claims • Demonstrated familiarity with clinical concepts related to a broad range of clinical conditions and disease states • Demonstrated familiarity with hypothesis testing, statistical methods, and/or comparative effectiveness study design and modeling