Remote 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.

This is not a reporting role. 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.

This position will report into the Senior Director of Ecommerce.

What you get to do:

Company-Wide Insight Leadership

• 
  
• 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 decisions insights should inform.
  
• 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.
  

Data Integrity, Metrics & Standards

• 
  
• 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.
  

AI-Enabled Analytics & Insight Workflows

• 
  
• 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.
  

Web, Customer & Commerce Analytics (Heap)

• 
  
• 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.
  

Cross-Functional Integration

• 
  
• 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 operatio