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ML Engineer — Demand Forecasting for Retail Chain
Elisa Conte
Full-time · Senior
About the role
We operate 280 retail stores across Central Europe. Our forecasting is done in Excel by regional managers. It's wrong. Not slightly wrong — expiry write-offs cost us €2M last year, and out-of-stock events cost us another €3M in missed revenue.
We need an ML engineer to build a proper demand forecasting system — product-level, store-level, accounting for seasonality, promotions, local events and weather.
Stack: Snowflake for data, dbt for transformations, we're open to LightGBM, Prophet, or neural approaches — whichever fits best. You'd own the full pipeline: data prep, model training, evaluation, and integration with our replenishment system.
Requirements
- – Proven experience with hierarchical or multi-store demand forecasting
- – Solid Python and SQL — our datasets are large
- – Experience with seasonal products and promotional lift modelling
- – Has integrated forecasting output into operational systems (not just notebooks)
- – Can communicate results clearly to non-technical buyers and merchandising teams
Job Type
Full-time
Level
Senior
Language
English
Salary Range
$100k – $140k / year
AI Expertise
AI & Machine Learning Engineers
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