Senior Director Data Science

About the Role

Optum is a global organization dedicated to improving health outcomes through technology-aided care. As the Senior Director of Data Science, you will lead the development and execution of a cutting-edge AI/ML strategy to enhance healthcare claims processing, improve operational efficiency, and reduce costs. This role involves end-to-end implementation of AI/ML solutions, from ideation and model development to deployment and optimization, leveraging deep domain knowledge of the healthcare claims lifecycle.

Primary Responsibilities

• AI/ML Strategy & Implementation: Develop and execute an AI/ML strategy specifically tailored to enhance healthcare claims processing, improve operational efficiency, and reduce costs. Lead the end-to-end implementation of AI/ML solutions.
• Healthcare Claims Domain Expertise: Apply deep knowledge of the healthcare claims lifecycle (processing, adjudication, encounters, appeals, grievances, operations) to identify opportunities for data science and AI.
• Strategic Leadership & Vision: Define and communicate a clear vision for how data science and AI will transform claims processing and operations. Drive innovation by championing new analytical approaches and technologies.
• Team Leadership & Development: Build, mentor, and manage a high-performing team of data scientists, ML engineers, and data analysts specializing in healthcare claims data. Foster a culture of continuous learning and best practices.
• Cross-Functional Collaboration: Partner closely with Claims Operations, IT, Finance, and other stakeholders to understand business needs and deliver impactful solutions. Effectively communicate complex AI/ML concepts to diverse audiences.
• Data Management & Governance: Oversee the acquisition, cleaning, and management of complex healthcare claims datasets, ensuring data quality, integrity, and compliance (e.g., HIPAA).
• Performance Monitoring & Optimization: Establish KPIs for AI/ML models, continuously monitor performance, and implement strategies for ongoing optimization.
• Enterprise Strategic Leadership Focus: Develop and execute org-wide AI/ML and Data strategies aligned with business goals, roadmaps, and technology transformation. Lead enterprise AI/ML strategy for healthcare analytics, claims automation, and operational excellence.
• Technical Innovation & Delivery Focus: Lead design, development, and hands-on implementation of advanced AI/ML solutions, including LLMs, Agentic AI, MCP, Generative AI, multimodal models, and predictive analytics for healthcare applications. Oversee enterprise-scale ML infrastructure, MLOps pipelines, and cloud integrations (AWS/Azure/GCP). Present outcomes, roadmaps, and technical vision to board and senior leadership.

Required Qualifications

• Master's in a quantitative field such as Statistics, Computer Science, Mathematics, Data Science, or a related discipline. Prior solid understanding of healthcare operations is a plus.
• Experience:
  • 18+ years of progressive experience in data science, with a significant focus on AI and Machine Learning.
  • 5+ years of experience in a leadership role, managing and mentoring data science or AI/ML teams.
  • Demonstrated success in developing and implementing AI/ML solutions (including Gen AI, Agentic AI, MCP, A2A) that have delivered measurable business value, preferably within the healthcare industry.
• Technical Skills:
  • Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (AWS, Azure, GCP) for building and deploying AI/ML solutions.
  • Expertise in a broad range of AI/ML techniques, including supervised and unsupervised learning, deep learning, natural language processing (NLP), and time-series analysis, preferably with a focus on their application to claims data.
  • Proficiency in programming languages and tools like Python or R, Agentic AI, Model Context Protocol (MCP), Agent to Agent Protocol (A2A) and relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch, Keras, XGBoost).
  • Familiarity with data warehousing, ETL processes, and database management (SQL).
  • Understanding of MLOps principles and tools for model deployment and lifecycle management.
• Leadership & Soft Skills:
  • Exceptional leadership, strategic thinking, and people management skills, with the ability to build and inspire high-performing teams.
  • Solid ability to translate complex business challenges in healthcare claims processing into actionable data science and AI solutions.
  • Excellent communication, presentation, and stakeholder management skills, with the ability to influence and gain buy-in from executive leadership and cross-functional teams.
  • Deep understanding of data governance, privacy, and security in the healthcare context (e.g., HIPAA compliance).
  • Proactive, results-oriented, and a passion for driving innovation in the healthcare domain.

Preferred Qualifications

• Deep expertise in the healthcare claims domain, including a thorough understanding of claims processing, operations, medical billing, coding, and related regulatory frameworks.
• Proven track record of leveraging healthcare claims data (e.g., X12, HIPAA 837/835) for analysis and model development.