VP of Enterprise Data, Analytics & AI

We are hiring a VP of Enterprise Data Analytics and AI!! The Vice President of Enterprise Data, Analytics & AI is responsible for building TIDI's enterprise data foundation and advancing the analytics and AI capabilities it enables.

This leader owns enterprise data strategy, governance, architecture, business intelligence, advanced analytics, data science, and the Databricks analytics platform.

The role will ensure internal and external data are trusted, connected, secure, and reusable so TIDI can move from retrospective reporting to predictive insight, intelligent automation, machine learning, and future AI-enabled decision support.

In partnership with Technology Services, this leader will establish the integration and MCP frameworks that allow approved AI models, agents, applications, and workflows to access governed enterprise data.

This role is focused on data, platforms, analytics, and AI data foundations.

This position can work remotely with in the US, but must be willing to come into any of our locations, as needed.

ESSENTIAL DUTIES AND RESPONSIBILITIES: Execute TIDI's enterprise data, analytics, and AI data-foundation strategy and multi-year roadmap.

Lead the Business Intelligence team and build capabilities across data engineering, advanced analytics, data science, and machine learning.

Establish, scale, and govern the enterprise data and analytics platform in Databricks.

Design an AI-ready architecture for structured and unstructured data, including reusable data products, semantic models, metadata, lineage, and business context.

Establish standards for data quality, master data, governance, security, privacy, access, retention, observability, and regulatory compliance.

Ensure data is prepared, governed, and accessible for reporting, predictive models, AI agents, retrieval, and automated workflows.

Partner with Technology Services to implement MCP and other secure integration patterns connecting enterprise data, systems, analytical tools, models, and workflows.

Relentlessly identify, evaluate, acquire, and integrate external data assets that improve market, customer, clinical, commercial, operational, and competitive decision-making.

Build a portfolio of high-value analytics, data science, machine learning, and AI use cases tied to measurable business outcomes.

Automate recurring data preparation, reporting, analysis, insight generation, and decision-support processes.

Establish model and analytical governance, including validation, explainability, monitoring, performance, lifecycle management, and human oversight.

Partner with business leaders to translate strategic questions into trusted data products, models, insights, and decisions.

Define and monitor value, adoption, data quality, platform reliability, speed to insight, model performance, and reuse of analytical assets.

Build, energize, and retain a high-performing, AI-enabled team that uses modern tools to increase speed, quality, and capacity.

Manage data providers, technology...