[Hiring] Director, Data Science @CenterWell

Role Description

As CenterWell's Director of Data Science (AI/ML), you will lead a technical team to manage model development for CenterWell's AI and machine learning portfolio. Working in close partnership with CenterWell's AI Product Management team, you will translate product priorities into validated AI solutions that improve measurement improvements in patient care and operational efficiency. You will sit at the center of a collaborative AI ecosystem – partnering with:

• Product to define what to build and pilot workflow integration.
• IT for data engineering and production deployment.
• Enterprise AI for generative AI capabilities, model development platforms, and responsible AI standards.
• Data governance/architecture to improve data structure underlying model development.
• Clinical and operations to ensure solutions support end-users.

Roles & Responsibilities:

• AI Model Development & Technical Proficiency:
  • Lead the development and validation of AI/ML model for both business segment specific and company wide applications (i.e., predictive modeling, NLP, agentic AI).
  • Maintain deep technical expertise in AI approaches, staying current on advances while applying rigorous judgement about what methods are appropriate for healthcare contexts.
  • Promote experimentation and rapid prototyping to validate technical feasibility and model performance before committing to full development cycles.
  • Balance a research mindset with production discipline, ensuring models are not just technically sound but operationally viable and maintainable.
  • Implement and rigorously follow enterprise-level frameworks for ongoing model monitoring and performance tracking in production environments.
• Product Partnership & Technical Consulting:
  • Define the technical vision and roadmap for the data science team, ensuring understanding of vertical and CenterWell priorities while establishing the operating model for scalable model development.
  • Collaborate with CenterWell's AI Product Management team to translate product priorities and use cases into technical approaches, timelines and resource requirements.
  • Provide technical consulting on feasibility, effort estimation, and trade-offs for potential AI opportunities.
  • Communicate model capabilities and performance characteristics to non-technical partners in clear, applicable terms.
  • Create technical roadmaps aligned with product priorities, ensuring the team has the right capabilities, tools, and infrastructure to meet strategic goals.
  • Engage with clinical and operational partners to understand domain context, validate model output, and ensure solutions address real-world needs.
• Team Leadership & Capability Development:
  • Develop a high-performing team of data scientists, creating a culture of collaboration and learning.
  • Build reusable frameworks, model templates and shared libraries that increase team productivity and ensure consistency across projects.

Qualifications

• 8+ years of data science experience with demonstrated expertise in developing and deploying ML models in production environments.
• Deep technical expertise in AI/ML approaches, with hands-on experience writing and reviewing product-quality code, and developing models from conception through production.
• 5+ years of management experience, including talent development and crossfunctional leadership.
• Experience partnering with product, engineering and partners to translate requirements into technical solutions.
• Experience with MLOps practices including model versioning, experiment tracking and product monitoring.
• Communicate complex technical concepts to non-technical audiences while maintaining credibility with senior data scientists and ML engineers.
• Demonstrated leadership in establishing technical standards, best practices, and team processes that move quality and efficiency.
• Can work Eastern Time Zone hours.

Requirements

• Experience in healthcare settings, working with EHR data, clinical terminologies, and healthcare-specific ML complexities.
• Familiarity with healthcare regulatory frameworks and their possible effects for model development and deployment.
• Advanced degree (MS or PhD) in computer science, (bio)statistics, informatics or related quantitative field.

Benefits

• Humana, Inc. offers competitive benefits that support whole-person well-being.
• Medical, dental and vision benefits.
• 401(k) retirement savings plan.
• Time off (including paid time off, company and personal holidays, paid parental and caregiver leave).
• Short-term and long-term disability.
• Life insurance and many other opportunities.