Principal Data Scientist, Manufacturing Analytics

Principal Data Scientist – Factory Intelligence

Location: 3350 E Hemisphere Loop, Tucson, AZ (BLDG M09)

Job Type: Hybrid (regular on‑site and off‑site)

Security Clearance: Active, transferable U.S. government‑issued security clearance (DoD Secret) required prior to start date; U.S. citizenship required.

Job Overview: As a Principal Data Scientist – Factory Intelligence, you will transform factory data into actionable intelligence that directly impacts production performance 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.

Key Responsibilities

• 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

• University degree or equivalent experience and a minimum of 8 years of relevant experience, or an advanced degree with 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.
• Demonstrated experience deploying, maintaining, and scaling machine learning models in production environments.
• Experience with relational database management and SQL development.
• U.S. citizenship with active and transferable security clearance as required.

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 role.

Equal Opportunity Employment

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.