Director of AI Analytics

CSC Generation

19h

About The Position

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 â 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, weâre all here for the same reason â 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.

Requirements

8+ years of experience in Analytics, Strategy, or Data Leadership roles.
Demonstrated experience leading analytics across multiple business functions.
Strong experience in commerce-driven businesses (retail, eCommerce, CPG, marketplace).
Comprehensive knowledge of all traffic acquisition channels and their downstream impact on site behavior, using that expertise to develop reliable forecasts that drive strategic decision-making.
Advanced SQL and strong analytical modeling capabilities.
Demonstrated experience designing and governing AI-enabled analytics workflows.
Strong capability to pressure-test AI-generated insights against data, customer behavior, and commercial logic.
Hands-on expertise with Heap or similar event-based web analytics platforms.
Comfort working with structured data formats (e.g., JSON), event schemas, and data instrumentation.
Experience defining KPI frameworks and resolving cross-functional metric misalignment.
Proven ability to translate complex data into clear, compelling stories that inform and influence executive decision-making - moving leadership from insight to action with confidence and conviction.
Track record of proactive insight generation, not reactive reporting
Ability to work standard Eastern Time business hours

Responsibilities

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 âwhat happenedâ to âwhy it happened,â âhow it happened,â and âwhat we should do next.â
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 â 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 operational execution.
Leadership & Enablement
Establish analytical standards that prioritize clarity, trust, commercial relevance, and decision impact.
Reduce reactive ad hoc work by building scalable, decision-focused reporting and automation frameworks.
Design the structure, workflows, and expectations for the analytics function.
Hire, mentor, and develop junior analytics talent once foundational systems are established.
Champion a modern, insight-driven analytics culture across the company.