Associate Data Scientist
Core
Build demand forecasting models for fashion and retail to anticipate consumer buying across brands, channels, and markets, including new products with no sales history.
Role type
Associate Data Scientist (Demand Forecasting)
Builds
Production forecasting models for product, size, store, channel, and market levels
Domain
Fashion & Retail / Time Series Forecasting
Deliverable
production ML models
Required skills
Demand forecasting in fashion/retail, Cold-start forecasting, Zero-shot and foundation models for time series, Time series statistical and deep learning methods, Python with ML libraries, Statistics and SQL, Generative AI basics
Preferred skills
Experience in fashion/apparel/retail, Databricks Lakehouse Platform, Forecasting at Scale with Spark, Pipelines and MLOps, Rapid prototyping
Technologies
PyTorch, TensorFlow, statsmodels, StatsForecast, NeuralForecast, Databricks, PySpark, Delta Lake, MLflow, Unity Catalog, Azure DevOps, Streamlit
Responsibilities
Build forecasting models for product, size, store, channel, and market levels; Contribute to cold-start forecasting for new products and markets; Benchmark and productionize zero-shot and foundation models; Collaborate with Data Engineers, DevOps, Product, Planning, and Merchandising
Seniority
Associate, mentored IC