Principal Engineer, Data Analytics and Machine Learning (Hybrid - Aguadilla, PR)

globalhr

Aguadilla (PR)

Hybrid

USD 120,000 - 160,000

Full time

12 days ago
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Benefits offered by this job

Medical, dental, and vision insurance
Three weeks of vacation
401(k) with employer matching
Employee Scholar Program
Life insurance and disability coverage
Employee Assistance Plan

Job summary

Collins Aerospace is hiring a Principal Engineer in Puerto Rico for data analytics and machine learning applied to aircraft services. You will lead analysis of complex datasets, develop predictive models, and guide teams across engineering disciplines to improve field performance and reliability.

The role involves mentoring engineers, driving digital transformation initiatives, and communicating technical insights to executives. Hybrid work with onsite and remote days is offered in Aguadilla, PR.

Qualifications

  • Typically requires STEM degree and 8 years of experience or advanced degree with 5+ years of experience.
  • Demonstrated professional English communication (verbal and written).
  • U.S. citizenship is required for access to program information.

Responsibilities

  • Lead analysis of engineering and aircraft datasets to improve performance and reliability.
  • Develop, train, and validate ML models for predictive maintenance and forecasting.
  • Define validation criteria and metrics for analytics and ML across programs.
  • Mentor junior engineers and promote best practices in analytics and ML.
  • Collaborate with design, reliability, and customer teams on data-driven recommendations.
  • Document technical work and present insights to leadership and customers.

Skills

Data analytics
Machine learning
Python
SQL
English communication
Leadership

Education

STEM degree
Advanced degree

Tools

NumPy/Pandas
TensorFlow/Scikit-learn
SQL databases
Tableau/Power BI

Job description

Date Posted:

2026-05-21

Country:

United States of America

Location:

US-PR-AGUADILLA-110 ~ Rd 110 N Km 28.8 ~ RD110

Position Role Type:

Hybrid

U.S. Citizen, U.S. Person, or Immigration Status Requirements:

U.S. citizenship is required, as only U.S. citizens are authorized to access information under this program/contract.

Security Clearance:

None/Not Required

Collins Aerospace is a leader in technologically advanced, intelligent solutions that help redefine the aerospace and defense industry. With a comprehensive portfolio and deep technical expertise, we help customers meet the demands of the global market. Join us and help shape the future of aerospace and defense.

The Global Engineering & Technology Center in Puerto Rico (GETC-PR) is seeking a seasoned Principal Engineer with advanced skills in Data Analytics and Machine Learning and a strong background in mechanical systems to lead mechanical and analytics developments analyzing complex aircraft services and engineering datasets. This role entails leveraging expertise in data analytics, machine learning, and mechanical engineering to extract actionable insights, develop predictive models, and lead initiatives that enhance field performance and reliability.

The ideal candidate will possess a deep understanding of mechanical engineering principles, such as structural behavior, dynamics, and thermal concepts, to interpret complex datasets and collaborate with subject matter experts. This role will also include mentoring junior engineers, helping establish best practices, and driving strategic initiatives that align with organizational goals, offering opportunities for leadership and high-impact contributions.

This position will sit at our Aguadilla, PR location. You must be residing in Puerto Rico at the time of starting employment. Relocation is not offered.

This role is categorized as hybrid, with 3 days onsite and 2 days remote following the schedule assigned by the Manager.

What YOU will do:
  • 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.
What YOU will learn:
  • You will learn about our growing engineering team in Puerto Rico; What we do? Who we support? How we work?
  • You will learn the technologies of today and tomorrow which we count on to maintain world leadership in the aerospace industry.
  • You will learn why people enjoy and feel fulfilled by working in our industry.
Qualifications you must have:
  • 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.
Qualifications We Prefer:
  • 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.
What We Offer

Some of our competitive benefits package includes:

  • 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!

Collins Aerospace, an RTX business, is a leader in technologically advanced and intelligent solutions for the global aerospace and defense industry. Collins Aerospace has the capabilities, comprehensive portfolio, and expertise to solve customers’ toughest challenges and to meet the demands of a rapidly evolving global market.

Join our growing engineering team in Puerto Rico, where you will provide critical support to all Collins SBUs, working on exciting programs and projects ranging from the development of the next generation of advanced concept ejection seats to the latest technologies for the U.S. warfighter.

WE ARE REDEFINING AEROSPACE.
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.

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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