Senior Data Scientist

Become a part of our caring community The Senior Data Scientist uses advanced analytics, machine learning, and predictive modeling to solve complex healthcare challenges and drive improved outcomes. You will develop data-driven solutions that support population health, utilization management, and quality improvement. You will collaborate with clinical, operational, and business partners to transform complex healthcare data into actionable insights that improve the experiences of Humana's members and providers. You will report directly to the Associate Director, Data Science.

Partner with Utilization Management (UM), clinical, and business teams to identify opportunities that improve healthcare quality, member outcomes, affordability, and provider experience. Design, develop, validate, and implement predictive models to identify clinical risk, utilization trends, quality gaps, and opportunities for intervention. Apply advanced statistical modeling, machine learning, and analytics techniques to support population health and healthcare decision-making. Build and maintain analytical datasets and features using medical, pharmacy, laboratory, and provider claims data. Collaborate with clinicians, clinical informaticists, and business stakeholders to translate complex business problems into analytical solutions. Evaluate model performance and communicate actionable insights and recommendations to technical and non-technical audiences. Research and scale innovative analytical approaches that improve healthcare outcomes and operational performance. Contribute to data science best practices, modeling standards, and reusable analytical frameworks across the organization. Understand Humana's objectives and independently manage work in a fast-paced and sometimes ambiguous environment. Use your skills to make an impact Required Qualifications Master's degree in Statistics, Biostatistics, Data Science, Economics, Mathematics, Computer Science, Clinical Informatics, or a related quantitative discipline. 4+ years of experience developing, validating, and implementing predictive models in healthcare, managed care, population health, or a related environment. Demonstrated experience independently developing predictive models that influenced clinical, operational, or financial outcomes. Advanced proficiency in Python, R, SAS, or similar programming languages used for statistical analysis and machine learning. Experience working with large, complex healthcare datasets, including claims, clinical, pharmacy, or laboratory data. Knowledge of statistical modeling, machine learning, model validation, and performance evaluation techniques. Demonstrated experience translating complex analytical findings and recommendations to technical and non-technical stakeholders.

Experience developing predictive models for risk stratification, utilization management, care management, or value-based care initiatives. Previous experience in a managed care setting. Experience with causal inference, causal machine learning, or advanced machine learning techniques such as NLP or deep learning. Experience working with big data technologies such as Spark or PySpark. Experience deploying and monitoring machine learning models in production environments. Familiarity with healthcare claims, clinical, pharmacy, laboratory, or EMR data (e.g. Epic). Work at Home Requirements: To ensure Home or Hybrid