AI Supply Chain Forecasting Engineer

Halvex Data

Remote · $100k – $130k / year · Full-time · Posted 5 months ago

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About the role

Predicting demand for 45,000 SKUs across 1,200 store locations with 94% accuracy sounds like an academic exercise. For our retail clients, it's the difference between $12M in dead stock and a clean inventory. We build the forecasting models that power purchasing decisions for mid-market retailers who can't afford to build their own data science teams. The models are the easy part — the hard part is everything around them. Data arrives late, formats change without warning, holidays shift demand patterns by 300%, and clients expect forecasts refreshed daily by 6 AM. You'll own the full lifecycle: feature engineering from messy POS data, model training on irregular time series, serving predictions through our API, and monitoring accuracy against actuals. The forecasting team is three engineers and one domain expert with 20 years in retail operations. You'll learn the domain fast because every model decision gets challenged by someone who knows what a realistic sell-through rate looks like.

Fully remote.

Responsibilities

Build and maintain demand forecasting models for retail clients
Engineer features from point-of-sale, inventory, and external data sources
Design and run backtesting frameworks for forecast accuracy evaluation
Serve daily forecast updates through production APIs
Handle data quality issues and build automated anomaly detection
Collaborate with domain experts to incorporate business rules into models

Requirements

3+ years in time series forecasting or demand planning
Experience with Python, SQL, and distributed computing frameworks
Familiarity with forecasting approaches: ARIMA, Prophet, neural time series models
Ability to build end-to-end ML pipelines from raw data to API endpoint
Comfort working with messy, real-world datasets