Manager, Data Science – Personalization & Recommendation Systems

• Manage, coach, develop, retain, and assess data scientists
• Partner with product, engineering, and design leads to use data-driven insights for decisions, goals, prioritization, and team objectives
• Lead end-to-end data science projects from problem formulation through model deployment
• Oversee experiments addressing targeted business questions
• Drive continuous improvement of key business metrics
• Translate data science outputs into business outcomes and delivered value
• Build strong business partner relationships and promote adoption of data science capabilities
• Monitor data science and technology trends and identify high-return investment opportunities
• Design and support deployment of machine learning models for personalized digital experiences
• Build and optimize recommendation and ranking systems balancing relevance, discovery, conversion, and revenue
• Develop multi-stage ranking systems with candidate generation and re-ranking
• Address cold-start and long-tail challenges in large product catalogs
• Partner with engineering on real-time personalization and scalable deployment
• Perform additional assigned tasks

• Experience with personalization & recommendation systems, search, or ranking problems at scale of millions of customers and products
• Experience developing sequential, transformer models and utilizing LLM models in production
• Understanding of collaborative filtering and learning-to-rank methods
• Experience optimizing models for GPU / distributed training
• Familiarity with large-scale datasets and production ML systems
• Exposure to real-time or low-latency serving environments
• Experience with vector search / ANN methods (e.g., FAISS, ScaNN) preferred
• Experience delivering end-to-end customized ML models in production environments
• Expertise in developing and deploying state-of-the-art algorithms using machine learning, statistical, and optimization methods
• Expert in modern analytics tools, programming languages, and cloud platforms such as Python, R, Spark, SQL, GCP
• Strong problem-solving skills with an emphasis on product development
• Experience proposing rapid experiments and iterating based on results
• Proven success guiding teams through unstructured technical problems
• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Applied Mathematics, or equivalent quantitative field
• 5+ years of progressively complex data science experience, or 2+ years with a Master’s degree
• 2+ years of managerial or leadership experience in data science or analytics organizations
• Retail experience preferred
• Marketing models preferred

Demonstrates expertise in managing and developing data science teams while delivering end-to-end machine learning solutions. Proficient in leveraging data-driven insights to drive business outcomes and optimize recommendation systems at scale.

• Machine Learning Model Development
• Personalization & Recommendation Systems
• Data Science Team Leadership
• End-to-End Project Management
• Statistical & Optimization Methods

• Python
• R
• Spark
• SQL
• GCP
• Collaborative Filtering
• Learning-to-Rank Methods
• GPU Optimization
• Vector Search
• ANN Methods

• Problem-Solving
• Coaching
• Collaboration
• Communication
• Team Development

• Data Science
• Retail Experience
• Marketing Models
• Statistical Analysis
• Quantitative Field

• Machine Learning Frameworks
• Analytics Tools
• Real-Time Serving Environments
• Large-Scale Datasets
• Production ML Systems