Director Product Discovery and Recommendations

Express•Columbus, OH

About The Position

The Director of Product Discovery and Recommendations will serve as the strategic architect of our AI/ML-powered personalization ecosystem. This role will define, manage, and operate the product discovery, search relevance, and recommendations systems of our commerce and marketing touchpoints through intelligent product, placement, and targeting algorithms. You will partner with Engineering, Merchandising, and Content teams to deliver predictive and adaptive systems that drive engagement, conversion, and customer value. You will integrate tried and true technologies such as collaborative filtering with cutting edge innovations such as semantic search and computer vision This role is at the intersection of technology, data, merchandising, and customer experience.

Requirements

Bachelor’s Degree in Computer Science, IT or equivalent work experience.
10+ years of experience with personalization and recommendation systems.
Scalable Impact: Proven track record of scaling personalization from pilot to 100% coverage, delivering significant incremental revenue (e.g., $100M+ scale).
Hybrid Technical Depth: Deep understanding of ML recommendation techniques and the ability to audit both internal code and vendor "black-box" models.
Strong understanding of personalization architecture: collaborative filtering, content-based recommendations, hybrid systems, and emerging AI/ML methodologies
Experience with A/B testing methodologies, experimentation frameworks, and statistical analysis
Strategic Sourcing: Expert in Vendor Management and technology integration, specifically within the AI/ML, Search, and Discovery space.
Action Oriented, Data-Driven Mindset: Mastery of KPI-driven analytics (AOV, RPV, Conversion) and experimentation frameworks. Ability to translate data insights into actionable product strategies, and the ability to influence at all organizational levels
Collaborative Leadership: Skilled at leading cross-functional teams of Data Scientists, Engineers, and UX Designers while simultaneously managing external partner implementation.
Background working with global, multi-brand, or omnichannel retail organizations
Familiarity with eCommerce platforms and digital merchandising systems

Responsibilities

Strategic Roadmap & Execution: Define the long-term vision for AI personalization. Orchestrate a hybrid ecosystem of proprietary internal data, AI/ML models, and 3rd party technology to drive Customer Acquisition, Retention, and LTV.
Design and Implementation: Lead the end-to-end development of recommendation engines across customer touchpoints including commerce (homepage, PDP, PLP, Cart) messaging (Email, Clientelling) and Mobile App. Define relevance, ranking, and filtering algorithms to improve product discoverability and conversion.
Technology Strategy: Actively scout, vet, and negotiate with AI/ML vendors. Lead Technology Assessments (RFPs) and Proof of Concept (PoC) testing to compare vendor performance against internal benchmarks.
Experimentation & Growth: Drive incremental revenue through rigorous A/B testing across PLPs, PDPs, and lifecycle marketing. Design "champion-challenger" tests to validate internal builds against external solutions.
Algorithmic & LLM Optimization: Partner with data science to refine sort ranking models and launch LLM-powered features (e.g., visually similar discovery), leveraging both internal expertise and external APIs.
Omnichannel Orchestration: Architect a unified experience by leveraging cross-channel marketing platforms to sync merchandise, commerce, and customer models external marketing and CRM automation tools.
Executive Stakeholder Management: Build business cases for investments in technology and translate complex algorithmic performance into actionable insights for C-level leadership