Principal Data Scientist – Factory Intelligence
Listed on 2026-07-13
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Software Development
Machine Learning/ ML Engineer, AI Engineer (Applied/Software), Data Scientist
Principal Data Scientist – Factory Intelligence
Location:
Tucson, Arizona. Work type:
Hybrid. U.S. citizens only. Security clearance:
Secret (required prior to start, interim clearance available).
- 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.
- University degree or equivalent experience and a minimum of 8 years of relevant experience, or an advanced degree and a minimum of 5 years of experience.
- Experience developing in Python (Num Py, Sci Py, scikit‑learn, scikit‑image) for production‑grade statistical or machine learning applications.
- 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 required prior to start; U.S. citizenship required as only citizens are eligible for a clearance.
- 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 Tensor Flow.
- 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 role.
Salary range: $107,500 - $204,500 USD.
Benefits are available to Hired applicants, including medical, dental, vision, life insurance, short‑term and 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 depend on the business unit and collective‑bargaining agreement.
RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. RTX provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans’ Readjustment Assistance Act.
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