optimize scalable data pipelines leveraging a hybrid SQL/Python architecture (dbt, Snowflake) to extract rich, localized temporal signals from high‐volume transactional retail data. End-to-End Deployment (MLOps): Partner with our engineers to transition your models from prototype into scalable, monitored, and reliable production pipelines using tools like … frameworks for training, tracking, deploying, and monitoring models in production (e.g., MLflow, Optuna, Prefect, or Airflow). Background in supply chainforecasting, enterprise AI, or retail analytics M.S. or Ph.D. in Computer Science, Artificial Intelligence, Statistics, Data Science, or a related quantitative field. Our Commitment to Diversity, Equity, Inclusionand Belonging (DEIB ...