Jobs / United States / Humana INC
Research Scientist 2
Humana INC · 🇺🇸 Louisville, KY
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 The Research Scientist 2 participates in research study design, analysis and interpretation of results, with special emphasis on statistical and analytical plan development; data acquisition, preparation, and management; statistical analysis and interpretation of findings. The Research Scientist 2 work assignments are varied and frequently require interpretation and independent determination of the appropriate courses of action. Humana’s Healthcare Quality & Reporting Improvement (HQRI) department is seeking a Research Scientist 2 to join a high-performing team dedicated to advancing predictive modeling and analytics in support of our Medicare and Medicaid business. The HQRI team plays a pivotal role within Humana, delivering insights that drive the effectiveness of risk adjustment initiatives. In this position, the Research Scientist 2 will partner with a senior research scientist to apply advanced statistical methods to rigorously evaluate the impact of risk adjustment programs and pilot projects. The findings generated will be critical in informing key business decisions and optimizing operational strategies. Additionally, the person in this role will collaborate with colleagues specializing in data science and actuarial analytics. We are seeking a candidate who brings complementary skills to the team, with the ability to learn from their teammates while contributing with their unique expertise in statistical analysis. Use your skills to make an impact Required Qualifications • Bachelor's degree in Computer Science, Data Science, Mathematics or a related quantitative field; • 2 years of experience applying statistical modeling, predictive analytics, machine learning, or quantitative research methods in a healthcare, insurance, consulting, or data science environment. • Strong programming skills in Python and SQL, with hands-on experience developing analytical and modeling solutions in Databricks, PySpark, or similar distributed data processing environments. • Experience building, calibrating, validating, and analyzing predictive models, including model performance evaluation, calibration techniques, and interpretation of modeling results. • Experience performing exploratory data analysis, feature engineering, and model performance assessment using large and complex datasets. • Ability to translate analytical findings into actionable business insights and effectively communicate results to technical and non-technical stakeholders. • Strong problem-solving, critical thinking, and collaboration skills, with the ability to work effectively in a cross-functional environment. • Must reside in or within reasonable commuting distance to Louisville, KY office. Candidates willing to self-relocate to Louisville also will be considered. Position requires working 2 days per week in office. Preferred Qualifications: • Master's degree or PhD in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative discipline. • Experience with healthcare analytics, including Medicare, Medicaid, Risk Adjustment, HCC modeling, Stars/HEDIS, provider analytics, or population health programs. • Experience developing, maintaining, or optimizing machine learning models in cloud-based analytics platforms such as Databricks. • Strong understanding of model calibration methodologies, including probability calibration techniques such as Platt Scaling, Isotonic Regression, and score normalization approaches. • Experience working with large-scale healthcare datasets, claims data, medical records, encounter data, or clinical data sources. • Familiarity with machine learning libraries such as scikit-learn, XGBoost, LightGBM, TensorFlow, or PyTorch. Additional Information This ro