Vice President, AI & Predictive Science

Responsibilities

• Develop and deploy models that directly contribute to identifying and recovering healthcare claims, with measurable business impact.
• Build, improve, and oversee implementation of a diverse suite of models, including classification, pattern mining, and rules-based approaches, to optimize workflows.
• Lead data flywheel strategy: Architect and scale systems that leverage feedback loops from claims, recovery outcomes, and enrichment data to continuously improve accuracy and efficiency.
• Translate research into products: Bridge the gap between technical R&D and commercial application, ensuring all AI/ML outputs can be operationalized and monetized.
• Team leadership and growth: Recruit, mentor, and manage a high-performing AI/ML team focused on scalable development, rapid iteration, and measurable outcomes.
• Collaborate cross-functionally: Partner with engineering, legal, and operations to integrate models into production environments and align with company goals.
• Stay ahead of the curve: Monitor AI, ML, and healthcare data trends to inform roadmap priorities and maintain competitive differentiation.

Qualifications

• Previous startup experience strongly preferred.
• 5+ years of experience in AI/ML leadership roles, including 3+ years at a high-growth or data-driven company.
• Deep expertise in multiple AI/ML paradigms, including classification, rule-based systems, association/pattern mining, NLP, and predictive modeling.
• Prominent record of developing and commercializing machine learning models into actionable, scalable, and commercializable products.
• Proficiency with large-scale data environments (1M+ rows) and modern ML/AI toolsets (e.g., Python, Databricks).
• Experience leading high-performing technical teams and building from the ground up – including being a team player (no job is too small for you to do or oversee).
• Healthcare claims, payment integrity, or legal tech experience strongly preferred but not required.
• Exceptional communication skills and the ability to translate complex technical ideas into business terms across teams.