Data Scientist Manufacturing Operations

Description

Drive global manufacturing strategy by turning complex capacity footprint and demand data into actionable insights. Enable decision-making capabilities of leadership to meet Hyperscale customer requirements. Build and maintain analytical models and scenario tools to optimize capacity identify constraints and support growth planning. Utilize AI to build Agents to enable quick iteration of potential scenarios. Collaborate with Engineering Operations Supply Chain and Finance to deliver data-driven recommendations that guide executive decisions and strategic footprint initiatives.

Responsibilities

• Design build and maintain scalable analytical frameworks and data models that enable rapid data-driven decision making related to capacity allocation footprint strategy and growth planning.
• Translate complex multi-source datasets into clear insights scenarios and recommendations for executive and customer-facing decision making.
• Build and maintain capacity throughput and utilization models across multiple product lines to identify constraints bottlenecks and scaling limits.
• Conduct scenario analysis sensitivity modeling and what-if simulations to optimize plant loading equipment utilization and capital investment decisions.

Capacity Planning & Optimization

• Collaborate with Engineering Operations Supply Chain and Finance to define analytical assumptions data definitions and decision criteria for strategic manufacturing initiatives.

Data-Driven Decision Intelligence

• Leverage and integrate data from MES ERP capacity planning tools and external sources to support strategic manufacturing analysis.
• Design and maintain cost utilization and capacity models that enable fast repeatable scenario evaluation and executive decision making.
• Translate complex datasets into clear insights visualizations and recommendations for senior leadership and customer-facing discussions.

Process Standardization & Scalable Analytics

• Enable scalable manufacturing strategies by embedding analytics into modular BoP approaches and digital factory initiatives.
• Support new product introductions by applying data-driven manufacturability and capacity-readiness assessments early in the design and planning process.
• Continuously improve analytical frameworks to enhance speed accuracy and consistency of global footprint and capacity decisions.

Education and Certifications

1. Bachelors Degree in: Data Science/Analytics/Statistics Computer Science Industrial Engineering Operations Research Manufacturing Engineering Supply Chain / Logistics Mathematics Physics or Economics (quantitative focus)

Requirements

• 3-5 years of experience in data analysis manufacturing analytics capacity planning or operations strategy.
• Proven experience with global manufacturing operations footprint optimization or capacity modeling.
• Experience building analytical frameworks scenario models or data-driven decision tools for executives or cross-functional teams.
• Demonstrated ability to work effectively in a cross-functional environment across a diverse global team
• Strong proficiency in AI Agent building/modeling SQL Python R or other data analysis tools.
• Experience with ERP/MES systems BI tools (Power BI Tableau) and capacity planning software.
• Expertise in statistical analysis scenario modeling forecasting optimization and KPIs for manufacturing or supply chain.

Years of Experience: 3-5

Travel Requirements: 10%

No Special Physical Requirements

Required Experience:

IC