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Principal Engineer, Data Analytics and Machine Learning
RTXPrincipal Engineer leading data analytics and machine learning initiatives for aerospace in Aguadilla, PR. Mentoring engineers and overseeing project developments while ensuring product performance and reliability.
Tech Stack
Tools & technologiesNumpyPandasPySparkPythonScikit-LearnSQLTableauTensorflow
About the role
Key responsibilities & impact- Lead and oversee the analysis of engineering and aircraft performance datasets, delivering actionable insights to improve product performance and reliability.
- Drive the development, training, and validation of machine learning (ML) models, with applications including predictive maintenance, service time estimation, and performance forecasting.
- Define and standardize validation approaches, acceptance criteria, and performance metrics for analytical and ML models across multiple programs.
- Guide and mentor junior engineers on data analytics and machine learning methodologies, fostering skill development and technical growth within the team.
- Serve as the primary technical liaison with engineering discipline owners, design teams, and external stakeholders to address critical engineering challenges and opportunities.
- Develop and implement best practices for data curation, cleaning, integration, and preparation for analytics and ML workflows.
- Oversee the analysis of strain gauge, structural, thermal, and flight/aircraft data, identifying trends, predictive indicators, and opportunities for system optimization.
- Lead collaborative efforts with design, reliability, service engineering, and customer support teams to provide data-driven recommendations that enhance product performance and address customer needs.
- Conduct advanced statistical analyses to assess quality, completeness, and integrity of engineering and enterprise data.
- Research, evaluate, and implement cutting-edge ML algorithms (e.g., supervised learning, unsupervised learning, clustering, anomaly detection) to solve engineering challenges and improve performance.
- Represent the organization in executive-level presentations, communicating technical recommendations and insights to leadership and customers.
- Develop and maintain technical documentation, presentations, and reports for technical and non-technical audiences.
- Advocate for and lead efforts in digital transformation, including leveraging digital thread, PLM systems, and model-based engineering workflows.
- Occasionally travel domestically and/or internationally to support project requirements, supplier engagements, or customer needs.
Requirements
What you’ll need- Typically requires a degree in Science, Technology, Engineering or Mathematics (STEM) and 8 years prior relevant experience or an Advanced Degree in a related field and minimum 5 years of experience.
- Demonstrated professional experience communicating in English (verbal and written).
- U.S. citizenship is required, as only U.S. citizens are authorized to access information under this program/contract.
- Expertise in data analytics workflows, statistical methods, and engineering data interpretation, with a proven record of solving complex technical challenges.
- Advanced knowledge of machine learning (ML) concepts, with demonstrated experience in developing, deploying, and validating models for prediction, classification, and anomaly detection.
- Advanced degree in Mechanical Engineering, Aerospace Engineering, Data Science, or a related field.
- Deep understanding of mechanical engineering principles, including structural behavior, dynamics, thermal concepts, and aircraft systems.
- Strong experience with Python for data analysis (e.g., NumPy, Pandas, PySpark) and familiarity with ML frameworks such as TensorFlow or Scikit-learn.
- Experience with finite element analysis (FEA), structural analysis, thermal concepts, dynamics, or instrumentation data interpretation.
- Proficiency with database tools and SQL for managing and analyzing datasets.
- Advanced experience with data visualization tools (e.g., Tableau, Power BI) and the ability to present insights effectively to diverse stakeholders.
- Expertise in specialized engineering data such as strain gauge, thermal, or flight/aircraft performance datasets.
- Experience with Agile methodologies and tools (e.g., JIRA, Confluence) and experience in cross-functional collaboration.
- Knowledge and hands-on experience with digital thread, PLM systems, or model-based engineering workflows to drive digital transformation initiatives.
Benefits
Comp & perks- Medical, dental, and vision insurance
- Three weeks of vacation for newly hired employees
- Generous 401(k) plan that includes employer matching funds
- Participation in the Employee Scholar Program (ESP)
- Life insurance and disability coverage
- Employee Assistance Plan, including up to 8 free counseling sessions.
- And more!
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
data analyticsmachine learningstatistical methodsPythonSQLdata visualizationfinite element analysispredictive maintenanceanomaly detectionengineering data interpretation
Soft Skills
communicationmentoringcollaborationleadershipproblem-solvingtechnical documentationpresentation skillsteam developmentanalytical thinkingcustomer engagement