URBN Senior Data Science Manager

Role Summary

URBN is seeking a Senior Manager of Data Science to serve as a strategic lead and operational force for a high-growth digital commerce initiative. You will guide a team of data scientists and analysts to empower intelligent decision-making across the product lifecycle, from fashion trend analysis and product concepts to marketing activation and forecasting.

 

In this role, you act as a full-service solution provider, managing projects from initial ideation through the deployment and maintenance of production services. You will serve as the senior-most data science leader on the initiative, owning delivery mechanics, talent growth, long-term technical strategy, and bringing unique AI innovations to fruition to power the next evolution of intelligent commerce at URBN.

Who You Are

• Technical Leader: You maintain a mastery of ML and GenAI architectures, allowing you to set technical direction for the team and contribute directly to the hardest problems when needed.
• Strategic Architect: You identify new development areas, shape multi-quarter technical roadmaps, and lead teams through complex problem solving to bring original ideas to life.
• People Leader: You excel at building teams and managing careers ranging from interns to Senior Data Scientists through the lens of technical excellence.
• Collaborative Partner: You translate complex AI concepts into clear business recommendations for diverse stakeholders and navigate a fast paced retail ecosystem with curiosity.

Role Responsibilities

Team Leadership & Talent Strategy

• Lead a team of data scientists, identifying strengths and development areas to foster a collaborative and inclusive environment.

• Own talent strategy and career development, providing one on one coaching, facilitating access to training, and delivering advice to help team members advance from individual contributors to technical leaders.

• Drive the recruiting and retention of top data science talent, ensuring the team's growth aligns with the scaling needs of the initiative.

Roadmap, Planning & Execution

• Serve as the end to end owner of project delivery, managing resources, timelines, and the operational cadence from inception to completion.

• Act as a primary interface for stakeholders, prioritizing initiatives to protect the roadmap and ensuring the team hits high impact milestones on time.

• Collaborate with peer Product Management and Engineering leaders to define and execute roadmaps, ensuring data science capabilities are integrated into the core platform strategy.

• Drive the end-to-end realization of unique AI initiatives, taking your own ideas and stakeholder needs from initial concept through to production-level GenAI, vision, and forecasting solutions.

Technical Excellence & Guidance

• Serve as the final technical sign off for the team's output, reviewing and approving technical approaches to ensure they are sound, scalable, and align with project goals.

• Maintain a hands-on presence by contributing directly to prototyping, code performance optimization, data engineering, and quality assurance to ensure production level reliability.

• Own the bridge between early-stage prototyping and production scale execution, translating high level technical vision into actionable software design.

• Collaborate with Engineering to ensure data sources and infrastructure are designed to support production level machine learning and custom reporting.

Role Qualifications

• 7+ years of experience in data science or analytics roles with demonstrated progression in scope and responsibility.

• 2+ years of leadership experience, specifically in managing data science teams, recruiting talent, and retaining top performers.

• Strong proficiency in Python and SQL for data manipulation, analysis, and code review.

• Experience with managing complex, large-scale data science projects from inception to production.

• Familiarity with the AI/ML lifecycle, including understanding model experimentation, monitoring, and maintenance in a production setting.

• Exposure to modern AI domains, such as Generative AI, Large Language Models (LLMs), Computer Vision, or multimodal embedding models is highly preferred.

• Bachelor's degree or higher in a quantitative discipline (Statistics, Mathematics, Computer Science, or related field).