At Lumenalta, we partner with forward-thinking organizations to build technology solutions that scale, delight users, and accelerate business growth. Our integral teams bring curiosity, commitment, and technical excellence to every project. We value transparency, autonomy, and impact—empowering every team member to do their best work.
We’re seeking an experienced Data Scientist with a strong applied statistics background and deep supply chain domain knowledge to join an enterprise manufacturing client.
Actively Hiring
We are hiring for a current opening on an active client project. This is a specific, presently open role. We review applications on a rolling basis and aim to move qualified candidates through our process promptly.
What You’ll Work On
Build demand forecasting models using time-series methods appropriate to supply chain variability—applying CV-based segmentation to classify materials by demand pattern and selecting the right forecasting approach per segment (e.g., smooth, erratic, lumpy, intermittent).
Perform demand variability analysis across material master and movement data—quantifying forecast error, identifying root causes of variability, and producing inputs that planning teams can act on directly in SAP.
Develop inventory pre-positioning and health/trend monitoring (HTMS) analytics, translating model outputs into actionable signals for supply chain planners—including safety stock recommendations, reorder point adjustments, and MRP parameter tuning.
Work directly with SAP ECC planning data—extracting and interpreting MD07 exception messages, purchase requisitions vs. PO receipts, and MRP-generated signals to understand how planners currently work and where predictive models create the most value.
Partner with cross-functional teams—supply chain planners, procurement, and operations—to translate domain knowledge into concrete model inputs, validate outputs against real planning decisions, and communicate findings in terms the business understands