Executive Director, Data & AI

Job Summary:

We are building an Intelligence Platform to serve as the single source of truth for insights, recommendations, and knowledge across the company. We are seeking a Data & AI leader to lead this transformation.

You will own the full arc from data foundation to business reporting to actionable intelligence: ingesting data from dozens of sources, resolving entities into a connected intelligence layer, powering AI and ML models on top that drive measurable commercial outcomes across both practice-level (B2B) and consumer-level (B2C) touchpoints. You will create clarity of intelligence, ensuring every insight is trusted, explainable, and directly tied to growth.

• Reporting to: Chief Technology Officer
• Location: Nashville, TN or Dallas, TX or Remote

• Execute the enterprise intelligence strategy as the knowledge and insight hub across the Revance portfolio
• Design and operationalize a self-reinforcing intelligence system where better data produces better models, smarter actions, and improved outcomes
• Translate business goals into a sequenced intelligence roadmap with measurable topline impact
• Establish clarity of intelligence: unified data unified semantics trusted insights automated action revenue lift

• Deliver AI-powered engines that can operate at scale
• Embed intelligence directly into commercial workflows (CRM, ordering, loyalty, digital platforms) so insights drive action at the point of decision
• Tie intelligence output to measurable outcomes: AOV, conversion, retention, share of wallet, pipeline velocity

• Design a modern data architecture incorporating knowledge graphs, entity resolution, vector databases, feature stores, and graph-based reasoning to create a connected intelligence layer
• Build and maintain an entity graph connecting components across the ecosystem with rich, queryable edges
• Own the semantic layer and metrics governance: consistent business definitions, reusable governed metrics, and decoupled business logic enabling self-service analytics and AI consumption
• Ensure platform scalability, reliability, governance, cost efficiency, and explainability at every layer

• Define and build the AI & Insights team and establish collaboration models with the data engineering function
• Lead and coordinate strategic vendors, ensuring all work aligns with long-term architecture, not just short-term deliverables; transition critical capabilities in-house over time
• Establish a culture of outcome-driven intelligence, not report generation - every model, metric, and pipeline must trace to business impact
• Own data governance, quality, lineage, observability, and compliance across all data domains, including AI guardrails (bias checks, human-in-the-loop, auditability)

• 10+ years in data, analytics, and AI, with at least 5+ years leading data or AI teams
• Proven track record of building compounding intelligence systems that directly drove revenue growth, ideally in B2B, B2C, or B2B2C environments
• Experience translating data strategy into executive narratives and cross-functional alignment; ability to make complex concepts intuitive for non-technical leaders
• Track record of building and scaling high-performing teams (data engineering, data science, analytics) from early stage to mature function

• Graph Strategy & Reasoning
  - Spearheaded enterprise graph strategy to move beyond relational constraints, architecting high-scale knowledge graphs and entity resolution frameworks that power complex graph-based reasoning for deep business insights
• Platform Leadership & Intelligence
  - Led modernization of the enterprise data platform to create an AI-ready environment; championed integration of generative AI capabilities directly into the data core
• Unified Intelligence Architecture
  - Architected a unified intelligence layer integrating vector databases, feature stores, and LLM-powered agentic workflows, enabling rapid deployment of production-grade AI across the organization
• Operational Excellence (Data Ops/MLOps) - Orchestrated world-class Data Ops and MLOps practices, leveraging Python, dbt, and modern orchestration (Airflow/Dagster) to establish a resilient, automated CI/CD pipeline for high-velocity data delivery and model management

• Experience operationalizing…