Role Description
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.
As a Research Scientist 2, you will:
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Design and execute outcomes studies to evaluate the clinical, utilization, and financial performance of clinical programs using observational and experimental methods.
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Apply causal inference, epidemiologic, and statistical methods to estimate program impact and generate credible evidence for decision-making.
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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.
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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.
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Partner with clinical, operational, financial, and business stakeholders to translate analytical insights into recommendations that inform clinical strategy, program design, contracting, and performance improvement.
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Develop high-quality analytical reports, presentations, and executive-level readouts for internal and external stakeholders.
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Translate complex methodologies and findings into clear, actionable business insights, communicating both implications and analytical limitations to technical and non-technical audiences.
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Independently determine appropriate analytical approaches and make sound methodological decisions in complex or ambiguous situations.
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Manage multiple analytical priorities while maintaining high standards for methodological rigor, accuracy, and reproducibility.
Qualifications
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Masterβs degree or PhD in Epidemiology, Biostatistics, Economics, Statistics, Health Services Research, Clinical Informatics, or a related quantitative discipline.
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2+ years of experience applying statistical, epidemiologic, econometric, or related quantitative methods to large, complex datasets.
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Strong foundation in causal inference and study design, including observational studies, comparative effectiveness research, and randomized controlled trials.
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Experience manipulating and analyzing data using Python, PySpark, R, SAS, or comparable analytical tools.
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Strong analytical thinking and structured problem-solving skills, with the ability to translate clinical and business questions into analytical approaches.
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Ability to select and apply appropriate analytical methodologies to moderately complex research and business questions, with guidance on more complex methodological challenges.
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Excellent written and verbal communication skills, including the ability to synthesize complex methodologies and findings into clear insights and recommendations for non-technical audiences.
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Strong attention to detail and organizational skills, with the ability to manage multiple priorities effectively.
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Demonstrated ability to work independently while collaborating effectively with multidisciplinary and cross-functional teams.
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Strong interest in healthcare and a passion for improving health outcomes and healthcare value.
Requirements
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Experience working in health insurance, managed care, healthcare analytics, or health services research.
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Strong understanding of healthcare payer economics, including healthcare utilization, medical cost, and total cost of care.
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Experience working with medical claims, pharmacy claims, laboratory data, eligibility/enrollment data, and clinical program operational data.
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Familiarity with clinical concepts across chronic and specialty conditions, such as cardiology, chronic kidney disease, oncology, or other high-cost clinical conditions.
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Experience evaluating clinical programs, care management interventions, or value-based healthcare initiatives.
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Familiarity with advanced causal inference and causal machine learning techniques, such as double/debiased machine learning, doubly robust estimation, and meta-learners.
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Proficiency in Python and PySpark, with experience working in Databricks and Microsoft Azure.
Benefits
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Medical, dental and vision benefits.
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401(k) retirement savings plan.
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Time off (including paid time off, company and personal holidays, paid parental and caregiver leave).
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Short-term and long-term disability.
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Life insurance and many other opportunities.
Company Description
Humana Inc. (NYSE: HUM) is a leading U.S. healthcare company. Through our Humana insurance services and our CenterWell healthcare services, we make it easier for the millions of people we serve to achieve their best health β delivering the care and service they need, when they need it.