Podimetrics

• Define and execute Podimetrics’ enterprise data and AI strategy, aligning investment, architecture, and delivery to the company’s mission and growth objectives. • Own the development and deployment of the AI-enabled Clinical and Data Platforms, including platform architecture, software development, data engineering, model development and deployment, and ongoing operations. • Lead the Clinical and Data Platform software engineering group, setting technical direction, delivery standards, and engineering culture in partnership with broader Product and Engineering leadership. • Build relationships with senior-level operations and commercial leadership to understand multifaceted business problems and develop analytical and platform solutions to complex issues. • Work closely and collaboratively with peers to solve problems, with hands-on ability to execute, and not just lead. • Build and continuously monitor reports, dashboards, and analytics products to track key healthcare quality, efficiency, and operational metrics. • Review policies for value-based programs, synthesize the information, and communicate the implications to our markets and executive leadership. • Define business and technical requirements for platform, database, and system development, and ensure architectural decisions are sound, scalable, and consistent with regulatory, security, and privacy requirements (including HIPAA). • Partner with Analytics leaders and peers, and with operational customers, to understand business problems, elicit requirements, develop analysis and reporting roadmaps, and deliver results according to plan while meeting or exceeding customer expectations. • Maintain a clear focus on delivering actionable insights and AI-enabled capabilities that help operational customers deliver better care, improve patient outcomes, and lower unnecessary costs and utilization. • Define and communicate a clear, compelling vision for the team that aligns with Podimetrics' mission and vision. • Provide leadership, motivation, coaching, feedback, and support to encourage and strengthen the development of an effective, high-performing, multidisciplinary team spanning data science, analytics, and software engineering. • Lead change through effective communication, explaining the connection and value to the organization while understanding the impact on the team to obtain commitment. • Serve as an executive-level representative for data, analytics, and AI with the board, investors, customers, and partners as needed.