Data Scientist

The Role 

Green Thumb Industries is building a data science function that powers real operational decisions — demand forecasting that drives inventory positioning, analytics science that surfaces what's happening in our stores, and feature engineering that makes every model smarter over time. 

This is a hands-on individual contributor role on a small, high-output, high-visibility team. You will spend your time building, testing, and maintaining ML models, engineering features, and translating data into answers that the business can act on. You will work closely with the Manager of Data Engineering, AI & ML, who will guide your technical direction and business context while you grow into shaping both. The systems are already starting to get built — your job is to push them further. 

This is a hybrid role and requires in office work 1 day per week every 2 weeks at our office in River North in downtown Chicago. 

Responsibilities 

ML Forecasting 

• Build, validate, and refine demand forecasting models for GTI's retail, wholesale, and other emerging business verticals across daily, weekly, monthly, and quarterly forecast horizons 

• Engineer new features for the Snowflake Feature Store — drawing from retail sales history, inventory movement, weather data, customer demographics, and external signals — to improve model accuracy across store, product, market and other dimensions 

• Develop and test new model candidates against GTI's established backtesting framework; interpret backtest results and surface findings to inform promotion decisions 

• Investigate forecasting errors and anomalies: identify when model performance degrades, diagnose root causes (data drift, structural breaks, new store openings, regulatory changes), and propose remediation 

• Conduct dimensionality reduction and principal component analysis to understand primary feature importance 

• Collaborate with the Manager to evolve the feature engineering roadmap — identifying signals worth building, data gaps worth closing, and model architectures worth exploring 

Analytics Science 

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