Role Description
The Senior Research Scientist applies statistical, epidemiologic, and causal inference methods to large, complex healthcare datasets to evaluate clinical program performance, identify drivers of outcomes, and inform strategic and operational decisions. This role will be part of the Quality & Cost Strategy Analytics team supporting the performance management and evaluation of clinical programs.
As a Senior Research Scientist, you will:
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Design and execute rigorous 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 broad or ambiguous clinical and business questions into well-defined analytical questions, hypotheses, and study designs.
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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.
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Understand broader department, segment, and enterprise strategies and connect analytical work to key operating and strategic objectives.
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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3+ 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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3+ years of experience manipulating and analyzing large datasets using Python, PySpark, R, SAS, or comparable analytical tools.
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Strong analytical thinking and structured problem-solving skills, with demonstrated ability to translate ambiguous business or clinical problems into rigorous analytical approaches.
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Ability to select and apply appropriate analytical methodologies to moderately complex to complex research and business questions.
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Excellent written and verbal communication skills, including the ability to synthesize complex methodologies and results into clear business insights and recommendations for non-technical audiences.
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Strong attention to detail, organizational skills, and ability to manage multiple priorities effectively.
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Demonstrated ability to work independently with minimal guidance while collaborating effectively across 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.