As we accelerate our transformation into an enterprise powered by data and AI, we are seeking a Senior Director of Data Science & AI to serve as the strategic architect and operational leader of our data science and artificial intelligence-based solutions. This role goes well beyond managing models鈥攊t is about shaping how AI fundamentally transforms how we understand our consumers, optimize our operations, and make decisions across every channel and market.
Reporting directly to the VP of Analytics & Planning, you will own the enterprise AI and data science strategy, build and scale a world-class team, and drive adoption of AI-powered solutions across merchandising, supply chain, marketing, consumer experience, and international expansion. You will be a key member of the analytics leadership team, influencing executive decision-making and championing a culture of experimentation and data-driven innovation across the organization.
What you'll get to do:
Enterprise AI & Data Science Strategy
- Define and own the multi-year AI and data science strategy aligned to enterprise growth priorities, presenting roadmaps and business cases directly to the C-suite and board.
- Establish the organization鈥檚 AI vision鈥攊dentifying where machine learning, generative AI, and advanced analytics create the highest-leverage impact across the value chain.
- Lead the evaluation and adoption of emerging AI capabilities (LLMs, agentic AI, computer vision, NLP) and determine fit-for-purpose applications across business domains.
- Drive the build-vs-buy strategy for AI/ML platforms and tools, partnering with engineering leadership to shape the technology ecosystem.
Operational Leadership & Execution
- Translate strategic priorities into an actionable portfolio of AI/data science initiatives with clear business KPIs, timelines, and resource plans.
- Own the end-to-end lifecycle of AI/ML solutions: ideation, experimentation, development, productionization, monitoring, and continuous improvement.
- Establish scalable MLOps practices including model versioning, automated retraining pipelines, drift detection, and governance frameworks.
- Create and maintain an AI use case registry that tracks initiative status, business value delivered, and prioritization across all domains.
Consumer Intelligence & Personalization
- Architect the enterprise consumer intelligence strategy鈥攗nifying customer data signals to build a holistic understanding of consumer behavior, preferences, and lifetime value.
- Drive production-grade AI solutions including:
- Advanced customer segmentation (behavioral, psychographic, ML-based clustering)
- Customer lifetime value modeling and predictive retention frameworks
- Hyper-personalized recommendations across web, app, email, and in-store
- Churn prediction & proactive win-back strategies powered by real-time signals
- Next-best-action engines for lifecycle marketing orchestration
- Multi-touch attribution & media mix modeling to optimize marketing spend
- Partner with Marketing, CRM, and Digital Product to embed AI into consumer-facing experiences and campaign optimization.
Cross-Functional Influence & Business Partnership
- Serve as the senior analytics thought partner to business leaders across Merchandising, Supply Chain, Retail, Wholesale, International, and DTC channels.
- Identify and champion AI-driven opportunities in demand forecasting, inventory optimization, assortment planning, pricing intelligence, and supply chain efficiency.
- Collaborate with Finance and FP&A to integrate predictive models into planning cycles, scenario analysis, and strategic decision frameworks.
- Influence and align with Data Engineering, Data Platform, and Enterprise Architecture teams to ensure infrastructure supports scalable, production-ready AI workloads.
- Represent the AI and data science function in cross-functional steering committees, vendor evaluations, and strategic planning sessions.
Team Building & Organizational Development
- Build, lead, and mentor a high-performing team of data scientists, ML engineers, and AI specialists across consumer, operational, and emerging AI domains.
- Establish a center of excellence for AI and advanced analytics with reusable frameworks, shared playbooks, and governed best practices.
- Create clear career development paths and a talent strategy that attracts and retains top-tier data science talent in a competitive market.
- Foster a culture of intellectual curiosity, rigorous experimentation, and business-outcome orientation across the team.
- Drive knowledge sharing and AI literacy initiatives to elevate data science capabilities across the broader analytics organization.
Measurement, Governance & Ethical AI
- Define and own the impact measurement framework for all AI initiatives鈥攖racking ROI, business value, and operational lift with rigor and transparency.
- Implement robust A/B and multivariate testing programs to validate personalization, targeting, and optimization strategies before scaling.
- Champion responsible AI practices including fairness, explainability, bias detection, and compliance with data privacy regulations (CCPA, GDPR).
- Establish AI governance standards including model documentation, approval workflows, and regular performance audits.