URBN Senior Data Scientist
URBN
- Philadelphia, PA
- Permanent
- Full-time
- Design and implement machine learning models to power various applications, potential including a combination of forecasting, optimization, multimodal data analysis, GenAI, and automation, working with complex, high-dimensional datasets.
- Develop multimodal representations from diverse data sources, including text and images, 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, supporting rapid decision-making in a fast-paced environment.
- Partner with Product Management to translate business needs into technical AI solutions that align with strategic goals.
- Test hypotheses and analyze the results of experiments to drive continuous improvement and efficiency.
- Lead the technical evaluation of external AI/ML tools and vendors, influencing decisions for the technology stack.
- Design and execute robust model validation strategies, including back-testing models against historical data, using strong SQL skills and an understanding of enterprise data warehousing (EDW) and organically generated sources.
- 5+ years of industry experience in data science, AI/ML, and predictive analytics.
- Strong proficiency in Python and SQL for data manipulation, analysis, and model development.
- Understanding of a broad range of machine learning techniques and algorithms, with familiarity with the e-commerce domain being a plus.
- Practical experience with areas such as computer vision, image understanding, multimodal embedding models, or large language models (LLMs).
- Proven success in developing and deploying production-level machine learning models.
- Experience with 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, particularly in contexts requiring speed and operational efficiency.
- Excellent communication, collaboration, and strategic problem-solving skills.
- Bachelors of master’s degree in quantitative field (e.g., Computer Science, Statistics, Engineering, Mathematics) or equivalent practical experience.