Senior Principal Data Scientist – Secret-Cleared, Mission-Critical

Northrop Grumman; Magna (UT); On-site; USD 135,000 - 203,000; Full time

Benefits offered by this job

Health insurance

Discretionary bonus

Paid time off

Long term incentives

Job summary

Northrop Grumman is seeking a Sr. Principal Data Scientist – Level 4 in Magna, UT to define the art of the possible from day one.

The role requires applying reliability and uncertainty quantification to solid rocket motor hardware design, production, and sustainment, working closely with engineering, quality, operations, and program management. The position emphasizes collaboration across cross-functional teams, building predictive cost models, and developing new tools and technology roadmaps

Qualifications

• Requires strong knowledge of reliability, probabilistic and Bayesian uncertainty quantification methods.
• Experience with statistics software and data science applications.
• Ability to learn and apply statistics to novel hardware-related problems.

Responsibilities

• Develop failure modes and effects analyses and model variability and probabilities of failure for components.
• Estimate manufacturing variability and apply statistical process controls.
• Support defect reduction and sustainment initiatives in production.
• Develop models and data for material properties used in design and testing.
• Analyze data from performance tests on solid rocket motor systems.
• Maintain databases and reports monitoring aging trends and service life estimates.

Skills

Statistical methods

R-based tools

Education

Bachelor's degree

Master's degree

PhD

Tools

Rstudio

Statistica

Job description

Northrop Grumman is seeking a Sr. Principal Data Scientist – Level 4 in Magna, UT to define the art of the possible from day one.

The role requires applying reliability and uncertainty quantification to solid rocket motor hardware design, production, and sustainment, working closely with engineering, quality, operations, and program management. The position emphasizes collaboration across cross-functional teams, building predictive cost models, and developing new tools and technology roadmaps