Director of AI Analytics

With 58 stores and the largest avocational cooking program in the US, Sur La Table offers an unsurpassed selection of exclusive and premium-quality goods for the kitchen and table – and the culinary expertise and inspiration to go along with it. Whether the job entails interacting with our customers, driving digital growth, or providing vital behind-the-scenes support, we’re all here for the same reason – to roll up our sleeves and create happiness through cooking and sharing good food.

Sur La Table is seeking a Director of AI Analytics to define how data, insight, and AI drive decision‑making across the company.

This role serves as the analytical hub of the organization, supporting eCommerce, Marketing, Finance, Retail, Merchandising, Inventory Planning, and Operations. While embedded within the eCommerce organization, the mandate of this role is company‑wide: to transform data into insight, insight into implications, and implications into clear recommendations that drive action.

It is a foundational leadership role responsible for establishing analytical standards, governing AI‑enabled workflows, ensuring data integrity, and elevating how decisions are made across the business.

Position will report into the Senior Director of Ecommerce.

• Serve as the primary analytics leader across eCommerce, Marketing, Finance, Retail, Merchandising, Inventory Planning, and Operations.
• Own problem definition for analytics – determining which business questions matter and what insights should inform decisions.
• Move analysis beyond “what happened” to “why it happened,” “how it happened,” and “what we should do next.”
• Proactively mine data to identify risks, opportunities, inefficiencies, and performance drivers.
• Influence senior leaders through clear implications and actionable recommendations.

• Own the integrity, governance, and usability of core commerce, customer, and operational datasets across platforms (eCommerce, POS, CDP, email, data warehouse).
• Validate insights using business context and commercial logic — not just technical correctness.
• Define, document, and continuously evolve company‑wide KPI frameworks in partnership with Finance and functional leaders.
• Identify and resolve cross‑functional metric misalignment to ensure a single, trusted understanding of performance.
• Establish standards for data quality, documentation, and analytical transparency across the organization.

• Leverage AI as a core component of advanced analytical work, including hypothesis generation, exploratory analysis, pattern detection, insight synthesis, and narrative development.
• Design, operationalize, and scale repeatable AI‑assisted workflows that support recurring company‑level decisions (growth, margin optimization, inventory productivity, forecast alignment).
• Establish validation frameworks to pressure‑test AI‑generated outputs against source data, historical performance, customer behavior, and commercial logic.
• Embed AI‑enabled insights into planning, forecasting, and executive performance reviews.
• Promote responsible, explainable, and outcome‑driven AI usage across analytics workflows.

• Own web and digital analytics strategy using Heap, including funnel performance, customer journey analysis, and conversion optimization.
• Ensure tracking integrity and event schema accuracy, including review of structured data formats (e.g., JSON, data layers) in partnership with Product Engineering.
• Translate behavioral data into commercial implications that influence merchandising, marketing, inventory, and operational decisions.
• Ensure behavioral insights are aligned with downstream systems and financial realities.

• Reconcile demand, margin, inventory, and operational perspectives into cohesive performance narratives.
• Support planning, forecasting, and performance alignment across Finance, Retail, Merchandising, and Operations.
• Challenge assumptions and reframe business narratives using data‑backed insight.
• Serve as a connector between commercial strategy and…