Senior Data Scientist – Factory Intelligence

RTX

. Develop statistical and machine learning solutions for manufacturing, test, quality, and production challenges .

Posted 9/23/2026full-timeTucson • Arizona • United StatesSenior💰 $107,500 - $204,500 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and deploying Python-based machine learning solutions and statistical models for manufacturing and engineering challenges. Proficient in data analysis, visualization, and mentoring technical teams while ensuring compliance with security clearance requirements.

Highest-signal resume keywords

Python For Data AnalysisMachine Learning Solutions DevelopmentApplied Statistics And Quantitative AnalysisRelational Databases And SQLMentoring Technical Professionals

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Statistical ModelingMachine LearningData AnalysisData VisualizationMLOps PracticesModel VersioningMonitoring And EvaluationLarge Language ModelsGenerative AITechnical Communication

Soft Skills

CollaborationProblem-SolvingTechnical Leadership

Tools & Technologies

NumPySciPyPandasScikit-LearnScikit-ImageMinitabRJMPSASAWS

Certifications & Qualifications

U.S. CitizenshipDoD Secret Clearance

Industry Keywords

Manufacturing DataEngineering DataQuality DataTest DataComplex Technical Datasets

Tech Stack

Tools & technologies

AWSAzureNumpyPandasPythonPyTorchScikit-LearnSQLTensorflow

About the role

Key responsibilities & impact

Develop statistical and machine learning solutions for manufacturing, test, quality, and production challenges
Explore large and complex datasets to identify patterns, process drivers, anomalies, and improvement opportunities
Build and deploy Python-based analytical and machine learning applications for engineers and factory teams
Partner with engineers, operators, and technical stakeholders to translate problems into practical data solutions
Develop visualizations and analytical tools that make complex data actionable
Establish sustainable approaches for deploying, monitoring, and maintaining machine learning solutions
Mentor data scientists and engineers and contribute to technical direction and best practices
Build expertise in factory and test data to identify opportunities for data science and automation
Transition successful solutions from prototypes into production to influence engineering and manufacturing decisions

Requirements

What you’ll need

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
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 with relational databases and SQL
Ability to communicate technical findings and recommendations to technical and non-technical stakeholders
Experience analyzing manufacturing, engineering, test, quality, or other complex technical datasets
U.S. citizenship
Ability to obtain and maintain a U.S. government-issued security clearance; active and transferable clearance required prior to start date
DoD Secret clearance type; ability to obtain interim clearance required prior to start date
Preferred: experience deploying or supporting machine learning models in production
Preferred: Python libraries including NumPy, SciPy, pandas, scikit-learn, or scikit-image
Preferred: Minitab, R, JMP, or SAS
Preferred: machine learning lifecycle and MLOps practices, including model versioning, monitoring, evaluation, and MLflow
Preferred: AWS or Azure
Preferred: PyTorch or TensorFlow
Preferred: large language models or generative AI
Preferred: mentoring technical professionals or providing technical leadership

Benefits

Comp & perks

Medical, dental, and vision insurance
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
Holidays
Annual short-term and/or long-term incentive compensation programs may be available