URBN Senior Data Scientist

Urban Outfitters, Inc.; Philadelphia (Philadelphia County); On-site; USD 90,000 - 150,000; Full time

Job summary

An established industry player is on the lookout for a Senior Data Scientist to lead the charge in developing AI-driven digital experiences. This pivotal role focuses on crafting machine learning solutions that enhance decision-making and drive innovation within the retail landscape. You will collaborate closely with leadership and cross-functional teams, utilizing your expertise in data science, AI, and predictive analytics to transform complex data into actionable insights. If you are passionate about shaping the future of intelligent retail and digital solutions, this opportunity offers a chance to make a significant impact in a dynamic environment.

Qualifications

• 5+ years of experience in data science and AI/ML.
• Strong proficiency in Python and SQL for data manipulation.

Responsibilities

• Design and implement machine learning models for fashion data.
• Collaborate with teams to integrate AI solutions into products.

Skills

Data Science

AI/ML

Predictive Analytics

Python

SQL

Time Series Analysis

Multivariate Forecasting

Computer Vision

Strategic Problem-Solving

Tools

Machine Learning Frameworks

Cloud-Based AI Infrastructure

Job description

Role Summary

URBN is seeking a Senior Data Scientist to develop AI-powered digital experiences. This individual will serve as the Algorithm Lead, identifying, grouping, and forecasting trends across various sources to enable advanced AI and machine learning solutions that drive innovation within our digital ecosystem. The role involves close collaboration with leadership, Product Management, and Engineering. The Senior Data Scientist will act as a technical Data Science owner, driving the development, implementation, and validation of AI/ML solutions for forecasting.

As Senior Data Scientist, you will play a pivotal role in developing ML solutions that empower multiple AI-first innovations at URBN, ensuring data-driven innovation enhances experiences and decision-making. If you are passionate about AI-powered digital transformation, predictive analytics, and machine learning, we invite you to help shape the future of intelligent retail and digital solutions at URBN.

Role Responsibilities

• Design and implement machine learning models to power fashion data clustering, forecasting, and automation, working with complex, high-dimensional datasets.
• Develop multimodal representations from text and image sources using modern machine learning techniques.
• Collaborate with cross-functional teams to integrate AI solutions into digital products and workflows, partnering with engineers to translate prototypes into scalable features and services.
• Guide data exploration and feature engineering to support high-performing models.
• Analyze large-scale data sets to generate actionable insights and recommendations.
• Partner with Product Management to translate business needs into technical AI solutions.
• Test hypotheses and analyze the results of clustering and forecasting experiments to drive continuous improvement.
• Lead the technical evaluation of external AI/ML tools and vendors, influencing decisions for the technology stack.
• Design and execute forecast validation strategies, including back-testing models against historical sales data, using strong SQL skills and an understanding of enterprise data warehousing (EDW) and organically generated sources.

Role Qualifications

• 5+ years of industry experience in data science, AI/ML, and predictive analytics.
• Strong proficiency in Python and SQL for data manipulation and analysis.
• Understanding of time series analysis and multivariate forecasting techniques, with familiarity with the e-commerce domain being a plus.
• Practical experience with computer vision, image understanding, multimodal embedding models, or large language models (LLMs).
• Proven success in developing production-level machine learning models.
• Experience in machine learning frameworks and cloud-based AI infrastructure.
• Hands-on experience with large-scale data processing, feature engineering, and automation.
• Ability to translate complex business challenges into data-driven solutions.
• Excellent communication, collaboration, and strategic problem-solving skills.