Data Scientist

• Build a BOM/configuration mix classifier to predict series and part-number mix from family-group-level demand.
• Develop models in parallel with the Lead Data Scientist across separate model tracks to avoid single-threaded development.
• Develop a net demand model incorporating salvage, rerun, and repair signals to calculate total manufacturing need.
• Implement feature engineering pipelines designed by the Lead Data Scientist.
• Conduct model experimentation, including hyperparameter tuning, ablation studies, and feature importance analysis.
• Create and maintain model cards, experiment logs, accuracy reports, and related technical documentation.

• Machine learning modeling experience across classification and regression.
• Strong Python skills with scikit-learn and LightGBM/XGBoost.
• AWS SageMaker experience, including training jobs and hyperparameter tuning.
• Ability to work effectively under the direction of a Lead Data Scientist while independently supporting separate model development tracks.
• Strong technical documentation practices, including model cards, experiment logs, and accuracy reports.

Nice to Have skills

• Multi-class classification experience.
• Exposure to manufacturing and inventory data.