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# Senior Principal Data Scientist -18872

- **Company:** Northrop Grumman
- **Location:** Roy, UT, United States
- **Experience:** Expert
- **Salary:** $135,000.0 - $202,600.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon S3, Data Analysis, Cloud Database, Customer Data Management, Data Architecture, Information Engineering, Python (Programming Language), Machine Learning, Reliability Engineering, SQL Databases, Snowflake, Reliability of Systems, Information Technology, Data Pipelines, Databricks
- **Published:** August 15, 2026
- **Apply:** https://www.techcareers.com/job.asp?id=3350891864&tx=UT5854THV&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* T04: 8 Years with Bachelors in Science; 6 Years with Masters; 4 Years with PhD.

Senior Principal Data Scientist: Bachelor's degree in Data Science, Statistics, Applied Mathematics, Computer Science, Mechanical/Aerospace Engineering, or a related STEM field and 8 years of experience; OR a Master's degree and 6 years of experience; OR a PhD and 4 year of experience.

U.S. Citizen and Ability to obtain a DoD Secret clearance.

2+ years of demonstrated experience developing cloud-based data architectures.

2+ years of demonstrated experience designing and implementing end-to-end data pipelines.

2+ years of demonstrated experience using Python, SQL, or other relevant data science programming languages.

1+ year of demonstrated experience designing predictive models.

Preferred Qualifications:

An active U.S. Government Secret level security clearance (at a minimum), to include a closed investigation date completed within the last 6 years.

Hands on experience with predictive maintenance, Prognostics and Health Management (PHM), or RCM methodologies.

Strong foundations in statistics, including survival/reliability analysis, time-series modeling, regression, and uncertainty quantification.

Strong foundation in data engineering and analysis, including structured (relational, time-series) and unstructured (logs, text, imagery) data types, data pipeline design, and hands-on experience managing real-world data quality challenges such as missingness, sensor drift, and irregular sampling.

Production experience with relevant Amazon Web Services (AWS) services (e.g., S3, Glue, SageMaker, Redshift, etc.), Palantir Foundry, Databricks, and/or Snowflake.

Proven expertise in artificial intelligence, demonstrated by hands on experience designing, building, and deploying machine learning models and AI solutions in production environments.

Experience with reliability engineering.

## Description

Develop data architectures in support of predictive modeling for a large-scale WS designed to be operational for multiple generations.

Create statistical, ML, and physics-based predictive models that forecast the Remaining Useful Life (RUL) of Line Replaceable Units (LRU) identified in CBM+ trade studies.

This includes processes like data exploration, model feasibility/accuracy evaluation, cost evaluation, model development & validation, and model demonstration.

Establish templates and standards for modeling and tracking CBM+ items and processes.

Support development of the CBM+ Program Plan.

Collaborate with both NG and customer data scientists to define a data architecture for the WS; ensure the CBM+ tech stack remains aligned with wider architecture tools and plans.

Engage directly with the customer in support of evolving program requirements.


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