Digital Operations & AI Lead

Evereve Incorporated•Edina, MN

10d•$85,000 - $135,000

About The Position

EVEREVE is hiring a Digital Operations & AI Lead to own the strategy, standards, and operating model for AI-enabled product data across its digital commerce ecosystem. The role ensures item data is accurate, governed, scalable, and prepared to support automation, search, recommendations, fulfillment accuracy, lifecycle management, and return reduction. Reporting to the Director of Site Merchandising, this position manages two Digital Operations, Item Data Specialists. It provides direction, prioritization, coaching, and process oversight for product setup and enrichment, promotional execution, gift cards, store listings, GEO accuracy, item lifecycle, and AI governance. The Lead partners with merchandising, marketing, technology, stores, fulfillment, analytics, and operations teams to improve data quality and scale AI-enabled digital operations.

Requirements

At least 7 years of experience in e-commerce operations, product data, digital merchandising, catalog management, master data management, retail operations, digital transformation, or a related field.
Experience leading people, projects, workflows, or cross-functional initiatives in a fast-paced digital commerce or retail environment.
Strong understanding of product data governance, taxonomy, structured attributes, data quality, catalog operations, lifecycle management, and digital publishing workflows.
Working knowledge of AI-enabled operations, automation, machine-readable content, search, recommendations, personalization, or data readiness for analytics and AI use cases.
Strong analytical, organizational, and communication skills, including the ability to translate strategy into clear standards, metrics, and work plans.

Nice To Haves

Experience with Shopify or similar e-commerce platforms.
Familiarity with PIM, MDM, ERP, CMS, digital asset, reporting, or workflow tools.

Responsibilities

Own the AI-enabled product data strategy and ensure item information is structured, governed, scalable, and ready for automation, search, recommendations, personalization, and future AI-enabled workflows.
Translate business needs into practical data requirements, standards, workflows, and operating procedures.
Identify ways to reduce manual work and improve accuracy through structured data improvements, rules-based workflows, automation, and AI-supported execution.
Develop and enforce governance standards for product attributes, metafields, taxonomy, naming conventions, descriptions, fit notes, lifecycle status, and publication readiness.
Establish quality standards and validation checkpoints to improve catalog accuracy, searchability, customer experience, reporting, and AI readiness.
Maintain documentation and training materials so the team and cross-functional partners apply standards consistently.
Oversee end-to-end item lifecycle operations, including setup, enrichment, publishing readiness, availability tracking, automated unpublish rules, seasonal archiving, and item status maintenance.
Monitor catalog readiness, data quality issues, lifecycle bottlenecks, and recurring process gaps; prioritize improvements that increase accuracy, speed, and scalability.
Guide the team in resolving incomplete, conflicting, outdated, duplicative, or inaccurate product data before it affects customers, fulfillment, reporting, or automation.
Oversee discount code setup, sale execution, promotional readiness, gift cards, store listings, local listings, and store GEO accuracy.
Ensure promotional and location-related data follows governance standards, is documented, and is executed accurately against business timelines.
Partner cross-functionally to troubleshoot issues affecting promotions, store data, customer experience, search, automation, or AI-enabled outputs.
Develop fulfillment standards connecting digital product data quality to accurate execution and customer expectations.
Manage digital return guidance by identifying product data, description, fit note, taxonomy, imagery, or operational gaps that may contribute to avoidable returns.
Use fulfillment and return feedback loops to improve descriptions, attributes, fit guidance, enrichment practices, and operational standards.
Define and maintain metrics for catalog readiness, data completeness and quality, publishing timeliness, lifecycle status, automation performance, returns, and team throughput.
Use reporting to identify process gaps, prioritize improvements, and communicate progress to stakeholders.
Lead continuous improvement efforts that reduce rework, improve speed to publish, and strengthen AI-ready operations.
Lead, coach, and prioritize work for two Digital Operations, Item Data Specialists.
Set expectations for accuracy, timeliness, documentation, governance adherence, AI-aware data practices, and cross-functional communication.
Balance daily execution with longer-term improvements to processes, standards, tooling, automation, and team capability.