Data Scientist – Predictive Modeling & Supply Chain Analytics

About the role

Lumenalta is looking for an experienced Data Scientist to design and implement predictive models that improve demand forecasting and inventory management for an enterprise manufacturing client. You will work closely with supply‑chain planners, procurement, and operations teams to turn complex SAP data into actionable insights.

Key responsibilities

• Build demand‑forecasting models using time‑series methods and segment materials by demand pattern (smooth, erratic, lumpy, intermittent).
• Analyze demand variability across material master and movement data, quantify forecast error, and provide actionable inputs for SAP planning.
• Develop inventory pre‑positioning and health‑trend monitoring analytics, delivering safety‑stock and reorder‑point recommendations.
• Extract and interpret SAP ECC planning data, including MD07 exception messages and MRP signals.
• Partner with cross‑functional teams to validate model outputs against real planning decisions.
• Perform exploratory data analysis on SAP transactional tables (MARC, MARD, EKKO/EKPO) to uncover demand patterns and leading indicators.
• Build and maintain reproducible analytical workflows in Databricks using PySpark, SQL, and notebooks.
• Establish best practices for model validation, segmentation logic, and presentation to ensure interpretability and trust.

Required profile

• 5+ years of experience as a Data Scientist or analyst in supply‑chain, manufacturing, or industrial planning.
• Strong foundation in applied statistics and time‑series forecasting.
• Deep domain knowledge of supply‑chain processes and SAP ECC data structures.

Required skills

• Python
• PySpark
• SQL
• Databricks
• SAP ECC (MD07, MARC, MARD, EKKO, EKPO)
• ARIMA, exponential smoothing, intermittent demand models
• Time‑series forecasting
• Demand variability analysis
• CV‑based material segmentation