URBN Data Scientist

URBN is seeking a Data Scientist to develop AI-powered visual experiences, with a primary focus on image and video generation. This individual will lead algorithm development and Image/Video Generative AI initiatives, leveraging generative AI models, multimodal data sources, and modern creative AI workflows to drive innovation across our digital ecosystem. The role involves close collaboration with leadership, Product Management, Creative, and Engineering teams.

As Data Scientist, you will play a pivotal role in building and orchestrating image and video generation pipelines that power AI-first innovations at URBN, from product imagery and creative content to virtual try-on and beyond. You will drive the development, implementation, and validation of generative visual AI solutions across a range of applications to support our product lifecycle.

This role blends deep technical fluency in generative models with a strong visual sensibility. The ideal candidate combines a solid machine learning foundation with hands-on experience in the rapidly evolving image and video generation landscape, including diffusion models, multimodal architectures, and GenAI workflow orchestration tools. You should be able to evaluate generated outputs not just quantitatively, but with a critical creative eye. If you are passionate about the intersection of generative AI and visual storytelling, and you stay current with the fast-moving landscape of image and video models, we invite you to help shape the future of intelligent, AI-native creative experiences at URBN.

• Design, implement, and optimize image and video generation pipelines using state-of-the-art models to produce high-quality visual content at scale.
• Build and maintain multi-model generative workflows using orchestration tools that chain together generation, inpainting, upscaling, style transfer, and conditioning steps into production-ready pipelines.
• Fine-tune and adapt image generation models using techniques such as LoRA, DreamBooth, ControlNet, IP-Adapter, and textual inversion to achieve brand-consistent, style-controlled outputs.
• Leverage multimodal and vision-language models for image understanding, visual analysis, automated tagging, and quality evaluation within generative workflows.
• Evaluate, prototype, and integrate emerging video generation models into creative and product workflows.
• Develop agentic AI pipelines that orchestrate multi-step visual content creation, from prompt generation and image synthesis to post-processing and delivery.
• Collaborate with cross-functional teams including Creative, Product Management, and Engineering to translate brand and business needs into scalable generative AI solutions.
• Lead the technical evaluation of new generative AI models, tools, and vendors as the landscape evolves, influencing decisions for URBN's visual AI technology stack.