Remote Senior Health Data Scientist (Causal Inference)

Humana, Inc.; Cheyenne (WY); Remote; USD 104,000 - 143,000; Full time

Benefits offered by this job

Bonus program

Job summary

Humana, Inc. is seeking a Senior Research Scientist to apply statistical, epidemiologic, and causal inference methods to large healthcare datasets, evaluating clinical program performance and identifying drivers of outcomes.

The role supports decision-making across clinical, operational, and business partners in a remote capacity. The candidate will design and execute outcomes studies, translate findings into actionable recommendations, and communicate results to non-technical audiences while

Qualifications

• Master’s degree or PhD in Epidemiology, Biostatistics, Economics, Statistics, Health Services Research, Clinical Informatics, or a related quantitative discipline.
• 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.
• 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, with demonstrated ability to translate 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 the ability to synthesize complex methodologies and results into clear business insights and recommendations for non-technical audiences.
• Strong attention to detail, organizational skills, and ability to manage multiple priorities effectively.
• Demonstrated ability to work independently with minimal guidance while collaborating effectively across multidisciplinary and cross-functional teams.
• Strong interest in healthcare and a passion for improving health outcomes and healthcare value.

Responsibilities

• Design and execute rigorous 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 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 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.
• Understand broader department, segment, and enterprise strategies and connect analytical work to key operating and strategic objectives.

Skills

Statistical analysis

Epidemiology

Causal inference

Problem solving

Communication

Education

Master’s or PhD in a quantitative field

Tools

Python

PySpark

R

SAS

Databricks

Azure

Job description

Humana, Inc. is seeking a Senior Research Scientist to apply statistical, epidemiologic, and causal inference methods to large healthcare datasets, evaluating clinical program performance and identifying drivers of outcomes.

The role supports decision-making across clinical, operational, and business partners in a remote capacity. The candidate will design and execute outcomes studies, translate findings into actionable recommendations, and communicate results to non-technical audiences while