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# Principal Data Scientist - Factory Intelligence

- **Company:** RTX
- **Location:** Tucson, AZ, United States
- **Experience:** Expert
- **Salary:** $107,500.0 - $204,500.0
- **Contract:** Contract
- **Skills:** Amazon Web Services, Microsoft Azure, Big Data, Data Visualization, Relational Databases, Database Development, R (Programming Language), Python (Programming Language), Machine Learning, Minitab, NumPy, Performance Tuning, Tensorflow, SAS (Software), SciPy, Test Data, Management of Software Versions, JMP (Statistical Software), Cloud Platform System, Pytorch, Large Language Models, Deep Learning, Scikit Learn, Statistics Packages, Data Analytics, Machine Learning Operations
- **Published:** July 9, 2026
- **Apply:** https://globalhr.wd5.myworkdayjobs.com/REC_RTX_Ext_Gateway/job/US-AZ-TUCSON-M09--3350-E-Hemisphere-Loop--BLDG-M09/Principal-Data-Scientist---Factory-Intelligence_01858487-1

## About the Role

Active and transferable U.S. government issued security clearance is required prior to start date. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance, Ability to obtain INTERIM U.S. government issued security clearance is required prior to start date, * Typically requires a University Degree or equivalent experience and a minimum of 8 years of prior relevant experience, or an Advanced Degree in a related field and a minimum of 5 years of experience

 * Experience developing in Python (NumPy, SciPy, scikit-learn, scikit-image) for production-grade statistical or machine learning applications (beyond academic examples)
 * Demonstrated experience deploying, maintaining, and scaling machine learning models in production environments
 * Experience with relational database management and SQL development
 * U.S. Citizen - Active and transferable U.S. government issued security clearance is required prior to start date. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance
*

Qualifications We Prefer:

 * Experience with statistical tools such as Minitab, R, JMP, or SAS
 * Strong knowledge of machine learning pipelines and MLOps practices (e.g., MLflow), including versioning, monitoring, and lifecycle management
 * Strong experience applying quantitative techniques (normalization, standardization, applied statistics) to analyze large, complex datasets and build deployable machine learning models, including in cloud environments such as AWS or Azure
 * Experience designing, training, fine-tuning, and deploying deep learning models using frameworks such as PyTorch or TensorFlow
 * Experience working with large language models (LLMs), including fine-tuning, evaluation, and deployment; or demonstrated deep knowledge of LLM concepts and architectures
 * Experience operating in a technical leadership or mentoring

## Description

* Collaborate with Engineering, Operations, and Quality teams to build and deploy predictive analytics solutions.
 * Develop models that directly impact yield, reduce variation, and support smarter decision-making.
 * Design, deploy, and maintain production-grade machine learning solutions.
 * Build intuitive data visualization tools and statistical analysis applications.
 * Partner with stakeholders to translate complex data into clear, practical insights.
 * Provide technical leadership and mentor junior data scientists and engineers.
 * Establish best practices in applied data science across the organization.
 * Become a subject matter expert in factory test data and uncover opportunities for improvement.
 * Solve challenging, data-driven manufacturing problems and deliver measurable production enhancements.
 * Work directly with customers to ensure data is fully leveraged to improve performance.
 * Contribute to scalable, production-ready data science solutions and help advance the organization's analytics standards.
 * Operate effectively in a fast-paced, multi-tasking environment.


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