Principal Data Scientist – Factory Intelligence

Date Posted:

2026-07-09

Country:

United States of America

Location:

US-AZ-TUCSON-M09 ~ 3350 E Hemisphere Loop ~ BLDG M09

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

At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world’s most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world.

Raytheon brings the strength of more than 100 years of experience and renowned engineering expertise to meet the needs of today’s mission and stay ahead of tomorrow’s threat. We deliver solutions that help our nation and allies defend freedoms and deter aggression, creating a safer, more secure world. Join us and help shape the future of aerospace and defense.

As a Principal Data Scientist – Factory Intelligence, you will play a key role in transforming factory data into actionable intelligence that directly impacts production performance. Working across Engineering, Operations, and Quality, you will lead the development and deployment of predictive analytics solutions that improve yield, reduce variation, and drive smarter decision-making at scale.

This is a hybrid role based in Tucson, Arizona.

What You Will Do:

Transform factory data into actionable intelligence that improves production performance.

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.

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 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

Please ensure the role type defined below is appropriate for your needs before applying to this role. This position is classified as:

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.