Executive Director, Data & AI

RevanceDallas, TX
Remote

About The Position

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.

Requirements

  • 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 (DataOps/MLOps) — Orchestrated world-class DataOps 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 recommendation systems at scale with measurable commercial lift
  • Understanding of loyalty ecosystems, CRM intelligence, and omnichannel personalization
  • Doctorate degree & 5 years of directly related experience OR Master’s degree & 7 years of directly related experience OR Bachelor’s degree & 9 years of directly related experience

Nice To Haves

  • Background in healthcare, life sciences, retail, or regulated industries is a strong plus

Responsibilities

  • 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)

Benefits

  • Competitive Compensation including base salary and annual performance bonus.
  • Flexible PTO, holidays, and parental leave.
  • Generous healthcare benefits, HSA match, 401k match, employer paid life and disability insurance, pet insurance, wellness discounts and much more!
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