Data Scientist
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Functional Scope: • BOM/Configuration Mix classifier — builds model to predict series and part-number mix from family-group-level demand • Parallel model development — works alongside DS Lead on separate model tracks to avoid single-threading • Net demand model — incorporates salvage, rerun, repair signals to calculate total manufacturing need • Feature engineering execution — implements feature pipelines designed by DS Lead • Model experimentation — runs hyperparameter tuning, ablation studies, feature importance analysis • Documentation — model cards, experiment logs, accuracy reports
Must Have:
- ML modeling (classification + regression)
- Python + scikit-learn + LightGBM/XGBoost
- SageMaker experience (training jobs, hyperparameter tuning)
- Comfortable working under direction of Lead DS
- Strong documentation habits
Nice to Have:
- Multi-class classification experience
- Exposure to manufacturing/inventory data
Job Title: Data Scientist (Models)
Top Skills Required:
Leads model design and training across all four use cases: New Demand forecast(DeepAR, XGBoost, Chronos-2), Install-Base Failure Prediction (Weibullsurvival analysis), BOM/Config Mix Prediction, and Total Demand Lifecycle. Hands-on model architecture plus team mentorship.