Senior Director, Clinical Data Science

Centene Corporation

Senior Director of Clinical Data Science transforming healthcare through advanced analytics and machine learning. Leading predictive modeling and program evaluation with a high-performing data science team.

Posted 5/29/2026full-timeRemote • Florida, Kansas, New York, South Dakota, Tennessee • 🇺🇸 United StatesSenior💰 $185,700 - $352,500 per yearWebsite

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

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.
Partner with clinical, operational, actuarial, and analytics leaders to translate business and clinical priorities into scalable data science solutions.
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.

Requirements

What you’ll need

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).
Strong programming and data science toolkit including Python, R, SQL, and modern development practices (e.g., Git-based version control).
Experience applying modern machine learning techniques, including deep learning or transformer-based approaches, to healthcare or large-scale data problems strongly preferred.

Benefits

Comp & perks

competitive pay
health insurance
401K and stock purchase plans
tuition reimbursement
paid time off plus holidays
flexible approach to work with remote, hybrid, field or office work schedules

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

predictive modelingmachine learningcausal evaluationstatistical modelingcausal inferencetreatment effect modelingpropensity score matchingquasi-experimental methodsdata analysisdata science

Soft Skills

leadershipmentoringcollaborationcommunicationstrategic thinkingproblem-solvingteam buildingorganizational skillsperformance managementmodel governance