Senior Research Scientist

Humana

1d•$104,000 - $143,000•Remote

About The Position

The Senior Research Scientist is part of Humana’s Quality & Cost Strategy Analytics team, which supports the performance management and evaluation of clinical programs. The role 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. The scientist designs and executes rigorous outcomes studies, conducts in-depth analyses to diagnose program performance, and translates complex findings into clear recommendations for clinical, operational, financial, and business partners. The work includes evaluating clinical, utilization, and financial performance; identifying opportunities to improve programs; and connecting analytical findings to clinical strategy, program design, contracting, and performance improvement. The position calls for sound analytical judgment, structured problem solving, independence, and the ability to navigate complex or ambiguous questions. This is a remote role. Occasional travel to Humana offices for training or meetings may be required. Home-based employees must have internet service with at least 25 Mbps download and 10 Mbps upload speeds and a dedicated workspace that protects member PHI/HIPAA information. The role is scheduled for 40 hours per week and is not eligible for work visa sponsorship.

Requirements

Master’s degree or PhD in Epidemiology, Biostatistics, Economics, Statistics, Health Services Research, Clinical Informatics, or a related quantitative discipline.
At least 3 years of experience applying statistical, epidemiologic, econometric, or related quantitative methods to large, complex datasets.
Strong foundation in causal inference and study design, including observational studies, comparative effectiveness research, and randomized controlled trials.
At least 3 years of experience manipulating and analyzing large datasets using Python, PySpark, R, SAS, or comparable analytical tools.
Strong analytical thinking and structured problem-solving skills, including translating ambiguous business or clinical problems into rigorous analytical approaches.
Ability to select and apply appropriate analytical methodologies to moderately complex to complex research and business questions.
Excellent written and verbal communication skills, including synthesizing complex methods and results into clear recommendations for non-technical audiences.
Strong attention to detail and organizational skills, with the ability to manage multiple priorities effectively.
Ability to work independently with minimal guidance and collaborate across multidisciplinary and cross-functional teams.
Strong interest in healthcare and a passion for improving health outcomes and healthcare value.

Nice To Haves

Experience in health insurance, managed care, healthcare analytics, or health services research.
Strong understanding of healthcare payer economics, including healthcare utilization, medical cost, and total cost of care.
Experience with medical claims, pharmacy claims, laboratory data, eligibility/enrollment data, and clinical program operational data.
Familiarity with clinical concepts across chronic and specialty conditions, such as cardiology, chronic kidney disease, and oncology.
Experience evaluating clinical programs, care management interventions, or value-based healthcare initiatives.
Familiarity with advanced causal inference and causal machine learning techniques, such as double/debiased machine learning, doubly robust estimation, and meta-learners.
Proficiency in Python and PySpark, with experience working in Databricks and Microsoft Azure.

Responsibilities

Design and execute outcomes studies evaluating 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.
Analyze medical and pharmacy claims, enrollment, and operational data to identify performance drivers, diagnose gaps, and uncover improvement opportunities.
Translate broad or ambiguous clinical and business questions into well-defined analytical questions, hypotheses, and study designs.
Partner with clinical, operational, financial, and business stakeholders to turn analytical insights into recommendations for clinical strategy, program design, contracting, and performance improvement.
Develop analytical reports, presentations, and executive-level readouts for internal and external stakeholders.
Explain complex methods and findings as actionable business insights, including their implications and analytical limitations, for technical and non-technical audiences.
Independently select analytical approaches and make sound methodological decisions in complex or ambiguous situations.
Manage multiple analytical priorities while maintaining methodological rigor, accuracy, and reproducibility.
Connect analytical work to department, segment, and enterprise strategies and operating objectives.