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# Senior Data Scientist - Factory Intelligence

- **Company:** RTX
- **Location:** Tucson, AZ, United States
- **Experience:** Expert
- **Salary:** $131,300.0 - $237,350.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Business Analytics Applications, Data Analysis, Microsoft Azure, Cloud Database, Data Systems, Database Applications, Relational Databases, R (Programming Language), Python (Programming Language), Machine Learning, Minitab, NumPy, Tensorflow, SAS (Software), SciPy, Test Data, JMP (Statistical Software), Pytorch, Large Language Models, Deep Learning, Pandas, Build Management, Scikit Learn, Statistics Packages, Machine Learning Operations, Software Version Control
- **Published:** September 26, 2026
- **Apply:** https://www.careerjet.com/job/us476938ea6e39b8485e578faccaf64de5/eaa

## About the Role

Security Clearance Status: 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 minimum 5 years experience.

 * Professional experience using Python for data analysis, statistical modeling, or machine learning
 * Experience developing machine learning or advanced analytical solutions beyond academic or experimental projects
 * Strong understanding of applied statistics and quantitative analysis
 * Experience working with relational databases and SQL
 * Ability to communicate technical findings and recommendations to both technical and non-technical stakeholders
 * Experience analyzing manufacturing, engineering, test, quality, or other complex technical datasets
 * U.S. Citizen - The ability to obtain and maintain a U.S. government issued security clearance is required. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance.

Qualifications We Prefer

 * You do not need to have experience in all of the areas below. Experience in one or more would be valuable:
 * Experience deploying or supporting machine learning models in production environments
 * Experience with Python libraries such as NumPy, SciPy, pandas, scikit-learn, or scikit-image
 * Experience with statistical analysis tools such as Minitab, R, JMP, or SAS
 * Knowledge of machine learning lifecycle and MLOps practices, including model versioning, monitoring, evaluation, and tools such as MLflow
 * Experience with cloud-based data or machine learning environments such as AWS or Azure
 * Experience with deep learning frameworks such as PyTorch or TensorFlow
 * Experience applying large language models or generative AI to practical business or engineering problems
 * Experience mentoring other technical professionals or providing technical leadership

## Description

Raytheon's Data, Analytics, and AI organization is seeking a hands-on Senior Data Scientist to help turn complex factory and test data into insights and solutions that improve how we build products. In this role, you will work closely with Engineering, Operations, Quality, and software teams to solve real manufacturing problems using statistics, machine learning, and data-driven applications. Your work will have a direct connection to production, from identifying the causes of process variation to developing predictive models and tools that help engineers make faster, better decisions.
You'll engage across the full data science lifecycle: exploring large, multifaceted datasets, developing and validating models alongside domain experts, and helping transition successful solutions into production environments. You will also play a key role in guiding how our organization applies modern analytics and AI techniques within manufacturing.
This is a role for someone who enjoys both the technical work and the problem-solving that happens when data meets the real world.
What You Will Do

 * Develop statistical and machine learning solutions that address manufacturing, test, quality, and production challenges

 * Explore large and complex datasets to identify patterns, process drivers, anomalies, and opportunities for improvement

 * Build and deploy Python-based analytical and machine learning applications that are used by engineers and factory teams

 * Partner directly with engineers, operators, and technical stakeholders to understand problems and translate them into practical data solutions

 * Develop visualizations and analytical tools that make complex data easier to understand and act on

 * Help establish sustainable approaches for deploying, monitoring, and maintaining machine learning solutions

 * Mentor other data scientists and engineers and contribute to the team's technical direction and best practices

 * Build deep expertise in factory and test data and use that knowledge to identify new opportunities for data science and automation