Sr. Director - Data Science

Senior Director Data Science 

Primary Responsibilities:

• AI/ML Strategy & Implementation: Develop and execute a cutting-edge 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, from ideation and model development to deployment and ongoing optimization

• Healthcare Claims Domain Expertise: Leverage deep knowledge of the healthcare claims lifecycle, including claims processing, adjudication, encounters, appeals and grievances and operations. Apply this domain expertise to identify opportunities for data science and AI to solve critical business problems within this space

• Strategic Leadership & Vision: Define and communicate a clear vision for how data science and AI will transform claims processing and operations. Drive innovation by identifying and championing new analytical approaches and technologies that can provide a competitive advantage

• 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, experimentation, and best practices in AI/ML development and deployment

• Cross-Functional Collaboration: Partner closely with Claims Operations, IT, Finance, and other key stakeholders to understand business needs, translate them into data science problems, and deliver impactful solutions. Effectively communicate complex AI/ML concepts and results to both technical and non-technical audiences, including executive leadership

• Data Management & Governance: Oversee the acquisition, cleaning, and management of complex healthcare claims datasets. Ensure data quality, integrity, and compliance with relevant regulations (e.g., HIPAA)

• Performance Monitoring & Optimization: Establish key performance indicators (KPIs) for AI/ML models and data science initiatives related to claims processing. Continuously monitor model performance, identify areas for improvement, and implement strategies for ongoing optimization

• Enterprise Strategic Leadership Focus

  • Develop and execute org-wide AI/ML strategy, Data strategy aligned with company business goals, Roadmap, and technology transformation

  • Lead enterprise AI/ML strategy for HealthCare analytics, claims automation, and operational excellence

  • Collaborate across functions-product, technology, operations, regulatory, executive leadership - to convert strategic priorities into scalable initiatives

• 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 real-world 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, shaping strategic direction through data and impact stories

  • Proven delivery of scalable, production-quality AI systems with measurable business value

  • Deep technical proficiency in ML frameworks, Python, cloud platforms, and responsible AI practices

  • Exceptional communication and stakeholder management skills for both executive and technical audiences

• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regard to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

Qualifications - External

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, etc., 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 Qualification:

• 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