Associate Director- Data Sciences

The Opportunity

The Associate Director of AI Solution Architecture leads the design, evaluation, and scaling of enterprise AI solutions, with a strong focus on healthcare use cases. This role combines hands‑on AI model evaluation, enterprise architecture leadership, and executive influence to ensure AI solutions are accurate, trustworthy, cost‑effective, and production‑ready. This role will be crucial for both Providence internal implementations as well as external health systems.

Key Responsibilites

Strategic And Thought Leadership

• Own Cyber AI solution architecture across GenAI, ML, SLMs, RAGs, etc. from data to deployment.
• Lead hands‑on evaluation of first‑ and third‑party AI models, especially for health and clinical use cases.
• Define and publish standard AI metrics: accuracy, bias/fairness, cost, latency, scalability, and time‑to‑development.
• Drive build vs buy vs embed decisions for AI platforms and vendors.
• Experience evaluating vendor AI solutions, foundation models, and platform‑embedded AI.
• Exposure to AI risk management frameworks, model cards, and audit readiness.
• Experience operating in large, complex enterprises or Global Capability Centers (GCCs).

Leadership

• Establish a strong point of view on AI observability, governance, and responsible AI.
• Influence senior leaders on AI strategy, investment decisions, and risk trade‑offs using evidence‑based insights.
• Guide and mentor AI engineers and data scientists on architecture choices, model evaluation, and solution options.
• Partner with security, compliance, and clinical stakeholders to ensure AI solutions meet enterprise and regulatory standards

Professional Experience/Qualifications

• 14+ years in AI/ML, data science, or advanced analytics, with senior experience in enterprise solution architecture and implementation high quality production grade solutions
• Proven experience evaluating and deploying AI models in regulated environments
• AI - 1-2yrs in AI Space on thought leadership
• Strong hands‑on expertise in model evaluation, benchmarking, and experimentation.
• Demonstrated ability to influence both executive leaders and senior engineers.
• Excellent ability to design, prioritize, plan and track large scale products.
• Understanding of AI governance, observability, and lifecycle management.

Preferred Experience

• Experience in People Management
• Healthcare