Manager, Data Science (Personalization & Recommendation Systems) (Remote)

About the Role As Manager, Data Science, you will manage a data science team and work with cross-functional partners to solve business challenges and promote data-driven decision-making with advanced data analysis and machine learning. What You’ll Do Attract, retain, develop, manage, coach and assess data scientists in a balanced team Work with product, engineering and design leads and leverage data-driven insights to make decisions, set goals, prioritize work and achieve team objectives Lead end-to-end data science projects from problem formulation to model deployment, ensuring high-quality deliverables that meet business needs Oversee the design of experiments that answer targeted questions Identify and drive continuous improvement of key business metrics within assigned team Translate data science outputs into business outcomes and value delivered Maintain strong business partner relationships to gain cross-organizational alignment, spur adoption and usage of data science capabilities and drive business outcomes Remain current on the latest trends and developments in data science and technology and identify areas that offer the greatest return on investment Additional tasks may be assigned Addendum Personalization & Recommendation Systems Accountabilities Design and support deployment of machine learning models to power personalized experiences across digital channels (e.g., homepage, PDP, cart, campaigns) Build and optimize recommendation and ranking systems balancing relevance, discovery, and business objectives (e.g., conversion, revenue) Develop multi-stage ranking approaches, including candidate generation and re-ranking Address cold-start and long-tail challenges in large product catalogs Partner with engineering to support real-time personalization and scalable deployment Skills & Experience Experience with personalization & recommendation systems, search, or ranking problems at scale of millions of customers and products Experience in 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 with delivering end to end customized ML models in production environment Required Expertise in developing and deploying state-of-the-art algorithms using machine learning and statistical and optimization methods to power various aspects of highly complex business models and deliver value Expert in using modern analytics tools, programming languages, and cloud platforms such as Python, R, Spark, SQL, GCP, etc. Strong problem-solving skills with an emphasis on product development Experience proposing rapid experiments to test the efficacy of new strategies or initiatives and iterating quickly 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 (or 2+ years with a Master’s degree) of progressively complex data science experience 2+ years of managerial or leadership experience in data science or analytics organizations Preferred Master's degree and/or Ph.D. Retail experience Marketing models