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StatisticsPharmacyPythonSpark
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Visa sponsorship, if you would relocate
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 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.
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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 Humana INC paid sponsored hires in similar roles2 certified filings for “Research Scientist 2” (Data Scientists) in IN: $86k–$112k, median $99k.
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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 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. 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 Humana INC paid sponsored hires in similar roles
- 2 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).
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
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Role Overview
The Research Scientist 2 applies statistical, epidemiologic, and analytical methods to healthcare data to evaluate clinical program performance, understand drivers of outcomes, and support clinical and business decision-making.
This role will be part of the Quality & Cost Strategy Analytics team supporting the performance management and evaluation of clinical programs. The Research Scientist 2 will design and execute rigorous outcomes studies, conduct deep-dive analyses to diagnose program performance, and translate complex analytical findings into clear recommendations for clinical, operational, and business partners.
The role requires strong analytical thinking, attention to detail, and the ability to approach moderately complex analytical questions independently while seeking guidance on more complex or ambiguous methodological issues.
Humana’s Quality & Cost Strategy Analytics team is seeking a Research Scientist 2 (Remote) to support the evaluation and performance management of clinical programs.
At Humana, we are focused on transforming the healthcare experience by improving health outcomes, managing healthcare costs, and advancing operational excellence. The Quality & Cost Strategy Analytics team operates at the intersection of clinical strategy, analytics, and enterprise value , using rigorous research and advanced analytics to inform clinical priorities and improve outcomes for our members.
Our team partners across the organization to identify opportunities, evaluate and optimize clinical solutions, and generate actionable insights that support high-value care. We apply rigorous performance measurement and research methods to understand what is working, for whom, and why , and translate those insights into opportunities for continuous program improvement.
Responsibilities
As a Research Scientist 2, you will:
• Design and execute outcomes studies to evaluate the clinical, utilization, and financial performance of clinical programs using observational and experimental methods.
• Apply causal inference, epidemiologic, and statistical methods to estimate program impact and generate credible evidence for decision-making.
• Conduct deep-dive analyses using medical and pharmacy claims, enrollment, and operational data to identify key performance drivers, diagnose performance gaps, and uncover opportunities for improvement.
• Translate clinical and business questions into clearly defined analytical questions and hypotheses, partnering with senior scientists as needed on more complex study designs and methodologies.
• Partner with clinical, operational, financial, and business stakeholders to translate analytical insights into recommendations that inform clinical strategy, program design, contracting, and performance improvement.
• Develop high-quality analytical reports, presentations, and executive-level readouts for internal and external stakeholders.
• Translate complex methodologies and findings into clear, actionable business insights, communicating both implications and analytical limitations to technical and non-technical audiences.
• Independently determine appropriate analytical approaches and make sound methodological decisions in complex or ambiguous situations.
• Manage multiple analytical priorities while maintaining high standards for methodological rigor, accuracy, and reproducibility.
Required Qualifications
• Master’s degree or PhD in Epidemiology, Biostatistics, Economics, Statistics, Health Services Research, Clinical Informatics, or a related quantitative discipline.
• 2+ years of experience applying statistical, epidemiologic, econometric, or related quantitative methods to large, complex datasets.
• Strong foundation in causal infer
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