Associate Vice President of AI Product Engineering

• Strategic Leadership: Develop and execute a strategic roadmap for machine learning initiatives that align with the health system's goals. Lead the creation of innovative AI/ML solutions to improve patient care, operational efficiency, and clinical outcomes. Communicate vision, gain buy-in, and foster collaboration with clinicians, operational leaders, and technology teams. Develop internal and external partnerships to foster collaboration and execution.
• Technical Design and Oversight: Lead the technical design of machine learning solutions tailored to meet business, clinical, and operational requirements. Ensure the robustness, scalability, and performance of ML models in production environments. Establish best practices for code development, version control, testing, and deployment of ML solutions. Implement CI/CD pipelines for ML deployment. Collaborate with security, infrastructure, and application teams to ensure seamless integration of ML solutions into workflows.
• Research & Development: Develop a pipeline of ML capabilities to explore, test, and develop with a view to production deployment and health system priorities. Stay informed about the latest advancements in machine learning and healthcare technology to guide continuous improvement and innovation. Communicate internally and externally, including publications, conference presentations, etc., as appropriate to advance our agenda.
• Trustworthy AI: Develop and execute on a roadmap to trustworthy AI, including MLOps, model monitoring and retraining, explainability, application standards for security and privacy. Ensure compliance with relevant and evolving regulations (e.g. HIPAA, coming FDA regulations).
• Team Management: Lead, mentor, and grow a team of data scientists, machine learning engineers, and software developers. Set high performance expectations and help team to achieve them. Create a positive culture that encourages collaboration and fosters innovation. Attract and retain top talent. Develop new leaders. Help others to find purpose amid uncertainty.
• Stakeholder Engagement: Develop credibility and trust with leaders by demonstrating expertise, aligning around shared goals, and acting as a thought partner. Develop a deep understanding of customer needs and apply that knowledge to prioritize projects, design solutions, and execute. Influence a wide-range of senior leaders inside and outside PennDnA. Articulate vision, build consensus, and inspire action to achieve outcomes.
• Continuous Improvement: Drive innovation and excellence across the organization, continuously seeking ways to enhance the use of data for informed decision-making. Stay abreast of industry trends, emerging technologies, and best practices in healthcare data analytics.

Education or Equivalent Experience:

• Bachelor's Degree is required. Education Specialization: e.g., Computer Science, Mathematics, Data Science, Machine Learning.
• 10+ years progressively responsible experience developing ML solutions, putting them into production, and scaling is required. 
• Master's Degree is required. Education Specialization: e.g., Computer Science, Mathematics, Data Science, Machine Learning.
• Ph.D. is preferred.

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