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The Public Interest Company

Vice President, AI & Predictive Science

Reposted 22 Hours Ago
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Remote
Hiring Remotely in United States
Senior level
Remote
Hiring Remotely in United States
Senior level
Lead vision, strategy, and delivery of AI/ML products that identify and recover third-party healthcare claims. Build and operationalize models, architect data flywheels, recruit and manage an AI team, collaborate cross-functionally, and translate technical work into measurable business outcomes and revenue.
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About the Company

The Public Interest Company is a comprehensive solution for identifying and recovering third party liability for health plans, risk-bearing provider groups, and self-funded employers. We combine AI and a legal tech platform to identify and recover claims that should have been paid by third party payers. We handle the entire recovery process, all while protecting members and streamlining operations. We empower healthcare organizations to maximize their financial performance, and recoup dollars towards care delivery, without adding administrative burden.
Role Overview
The Vice President of AI & Machine Learning will lead the vision, strategy, and execution of all AI/ML initiatives across the company. This role is responsible for transforming data into actionable, commercialized products that enhance the company’s ability to identify, pursue, and recover healthcare claims tied to third-party liability.

This is not a research and development role; This leader must balance deep technical expertise with business acumen, ensuring every model and product translates directly into operational efficiency, recoveries, and revenue.

This hire will also be responsible for designing and overseeing systems that capitalize on rich, proprietary data sets, that include healthcare claims, third-party enrichment, and legal information – harnessing a data flywheel effective to continuously improve and optimize models across the business.

Responsibilities

  • Productize AI/ML capabilities: Develop and deploy models that directly contribute to identifying and recovering healthcare claims, with measurable business impact.

  • Model development and innovation: 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.

  • Proven 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.

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