Data Scientist - Manufacturing Analytics (Secret Clearance)

Northrop Grumman; Town of Florida (NY); On-site; USD 87,000 - 131,000; Full time

Benefits offered by this job

9/80 Work Schedule

Education Assistance

Training and Development

Paid Time Off

Health Plan

Job summary

Northrop Grumman is seeking a Data Scientist in Apopka, FL to support manufacturing operations and drive data-driven improvements. You will extract MES data, create production metrics, and develop interactive dashboards using Python, SQL, Power BI, and Tableau to enable informed decision-making across engineering, production, and supply chain.

The role emphasizes collaboration with frontline teams, a focus on cost reduction, and the deployment of scalable analytic solutions in a fast-paced

Qualifications

• Bachelor's degree in a STEM-related field or higher with relevant experience.

Responsibilities

• Provide cross-functional support to manufacturing and engineering teams to improve processes and reduce costs.
• Utilize MES data to develop production metrics and dashboards for cost, cycle time, and throughput optimization.
• Develop data visualizations using Python/R, Power BI, and Tableau to communicate insights to business partners.
• Lead data-driven initiatives and digital transformation efforts, including AI adoption where applicable.
• Build scalable models to optimize product flow under capacity constraints and align SAP/MRP with executable plans.

Skills

Tableau development

Interactive dashboards

SQL

MES data

Data analytics

Python

Power BI

SAP

MRP systems

ERP systems

Education

Bachelor's degree in STEM

Master’s degree

Tools

SAP

Microsoft Excel

Job description

Northrop Grumman is seeking a Data Scientist in Apopka, FL to support manufacturing operations and drive data-driven improvements. You will extract MES data, create production metrics, and develop interactive dashboards using Python, SQL, Power BI, and Tableau to enable informed decision-making across engineering, production, and supply chain.

The role emphasizes collaboration with frontline teams, a focus on cost reduction, and the deployment of scalable analytic solutions in a fast-paced