Date Posted:2026-09-23
Country:United States of America
Location:US-AZ-REMOTE
Position Role Type:Hybrid
U.S. Citizen, U.S. Person, or Immigration Status Requirements: 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
Security Clearance Type: DoD Clearance: Secret
Security Clearance Status: Ability to obtain INTERIM U.S. government issued security clearance is required prior to start date
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
- Your work will not stop at a notebook or prototype. Successful solutions will be used to influence real engineering and manufacturing decisions.
This is a hybrid role based in Tucson, Arizona.
Qualifications You Must Have - 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
What We OfferOur values drive our actions, behaviors, and performance with a vision for a safer, more connected world. At RTX we value: Safety, Trust, Respect, Accountability, Collaboration, and Innovation.
Learn More & Apply Now!Please consider the following role type definition as you apply for this role.
Hybrid: Employees who are working in Hybrid roles will work regularly both onsite and offsite. Ratio of time working onsite will be determined in partnership with your leader.
As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote.The salary range for this role is 107,500 USD - 204,500 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills.
Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement.
Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company's performance.
This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply.
RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window.
