Senior Director, Clinical Data Science

Centene Corporation•Remote-FL, NE

2d•$185,700 - $352,500•Hybrid

About The Position

The Senior Director of Clinical Data Science leads the strategy, development, and deployment of advanced analytics and machine learning models that power clinical decision-making across the organization. This role is responsible for both the development of predictive and AI-driven models that identify clinical risk and prioritize interventions, as well as the rigorous evaluation of clinical programs using causal inference and program evaluation methodologies.

Requirements

Bachelor's Degree in a quantitative discipline such as Statistics, Biostatistics, Informatics, Mathematics, Computer Science, Public Health, or Economics or four (4) years of experience in lieu of degree.
8+ years years of data analysis, statistics or related experience.
Deep experience developing and deploying predictive models using large healthcare datasets, including claims and/or electronic health record data.
Strong expertise in statistical modeling, machine learning, and causal inference methods used to evaluate program effectiveness (e.g., treatment effect modeling, propensity score matching, quasi-experimental methods).
Experience evaluating care management, population health, or value-based care programs.
Strong programming and data science toolkit including Python, R, SQL, and modern development practices (e.g., Git-based version control).
Proven leadership, stakeholder management, and executive communication skills, with the ability to influence clinical, operational, and financial leaders.

Nice To Haves

Master's Degree preferred.
Experience applying modern machine learning techniques, including deep learning or transformer-based approaches, to healthcare or large-scale data problems strongly preferred.
Demonstrated success translating advanced analytics into operational workflows and measurable clinical and financial outcomes strongly preferred.

Responsibilities

Lead the enterprise strategy for clinical data science, including predictive modeling, machine learning innovation, and causal evaluation of clinical programs.
Develop and deploy advanced models that identify, stratify, and prioritize members for clinical and care management interventions.
Oversee development of models for high-risk and rising-risk identification, avoidable utilization, chronic condition progression, and care management prioritization.
Advance the organization’s AI capabilities by applying modern machine learning approaches, including deep learning and transformer-based models, to large healthcare datasets.
Lead rigorous evaluation of clinical programs using causal inference and quasi-experimental methods such as treatment effect modeling, propensity score matching, and difference-in-differences.
Establish analytic frameworks to quantify clinical outcomes, cost savings, and ROI from care management and other intervention programs.
Partner with clinical, operational, actuarial, and analytics leaders to translate business and clinical priorities into scalable data science solutions.
Ensure models are embedded into operational workflows and aligned with care management capacity, intervention types, and clinical priorities.
Establish standards for model governance, monitoring, and performance management to ensure regulatory compliance, fairness, and responsible AI practices.
Build, lead, and mentor a high-performing team of data scientists.
Performs other duties as assigned.
Complies with all policies and standards.