Job Summary:

Revance is 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

What You’ll Do

Execute the Intelligence Vision & Strategy

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

Power Commercial Intelligence & Growth Engines

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

Architect a Scalable Intelligence Platform

Design a modern data architecture that connects data across many sources into a coherent, well-modeled intelligence layer
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

Build & Lead the Intelligence Organization

Define and build the AI & Data Engineering team and establish collaboration models with other stakeholders
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 - 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)

What You’ll Bring

Strategic & Leadership

10+ years in data, analytics, and AI, with at least 5+ years leading data or AI/ML 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

Technical Architecture & Execution

Platform Leadership & Intelligence — Led modernization of the enterprise data platform to create an AI-ready environment; championed integration of ML/LLM capabilities directly into the data core
Unified Intelligence Architecture — Built a unified data layer that brings signals from many different source systems together into a single, trusted source of truth, creating the foundation that analytics and AI/ML models run on.
Operational Excellence (DataOps/MLOps) — Established disciplined DataOps and MLOps practices, with automated, well-tested pipelines that deliver data reliably and keep models monitored and maintained once they are in production.

Domain & Commercial Intelligence

Experience operationalizing AI enabled recommendation systems at scale with measurable commercial lift