Data Science Engineering Intern

In This Role, Your Responsibilities Will Be

• Develop a Power BI dashboard that predicts future past-due backlog based on

Customer Required Date (CRD), Planned Ship Date (PSD), model code, value stream, and material status, enabling planners to answer, "What will be late next month?" with data-driven confidence.

• Build weekly projected late backlog forecasts, top model code risk heat maps,

and simulation tools that quantify the impact of material availability, capacity constraints, and scheduling decisions on backlog recovery.

• Create a predictive surge capacity model for low-volume product lines (e.g.,

CMFHC) that identifies demand mix variation, highlights bottlenecks by operation, and produces growth scenario analyses to guide investment prioritization and lead time stability.

• Apply data science methodologies, including statistical modeling,

forecasting, and visualization, to translate complex operational datasets into actionable insights for planners, operations leaders, and SIOP discussions.

• Collaborate with cross-functional teams including supply chain planning,

operations, and engineering to validate models, gather requirements, and ensure analytical tools align with business priorities and decision-making workflows.

• Participate in multiple analytical projects at various stages, from data

exploration and model development to dashboard deployment and user training, gaining a comprehensive understanding of the data science project lifecycle in a manufacturing context.

Who You Are

• You are analytically minded and naturally curious, energized by turning raw

data into clear, actionable insights. You take initiative in exploring new tools and methodologies, and you're not afraid to dive into ambiguous problems to find structure and meaning. You communicate complex findings in ways that resonate with both technical and non-technical audiences. You thrive in collaborative environm