Engineer II, Data Analytics & Machine Learning (Hybrid - Aguadilla, PR)

Prattwhitney; Aguadilla (PR); Hybrid; USD 75,000 - 110,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

3 weeks vacation

401(k) with employer matching

Employee Scholar Program

Life insurance

Disability coverage

Counseling services

Job summary

RTX in Aguadilla, PR is seeking a Data Analytics Engineer to analyze aircraft services data and develop predictive models for forecasting, reliability, and service improvements. The role blends hands-on data work with collaboration across engineering teams and occasional travel.

The position requires a STEM degree with 2+ years of relevant experience, strong English communication, and practical ML, Python, and data analytics skills.

Qualifications

• Degree in STEM with 2 years of relevant experience or an advanced degree.
• Professional experience communicating in English (verbal and written).
• U.S. citizenship is required.
• Experience in data analytics workflows, statistical methods, and engineering data interpretation.
• Hands‑on experience with Python for data analysis (NumPy, Pandas, PySpark).
• Practical knowledge of machine learning concepts with model development and validation.
• Foundational understanding of mechanical engineering principles or aircraft systems.
• Strong analytical and problem‑solving abilities with clear communication to diverse audiences.
• Proficiency with Microsoft Office tools.

Responsibilities

• Analyze engineering and aircraft performance datasets to generate actionable insights for product performance and reliability.
• Perform data curation, cleaning, integration, and preparation for analytics, modeling, and machine learning workflows.
• Work with strain gauge, structural, thermal, and flight/aircraft data to extract features, identify trends, and detect anomalies or predictive indicators.
• Develop, train, and validate ML models for predictive maintenance, service interval estimation, and performance forecasting.
• Define validation methods, acceptance criteria, and performance metrics for analytical models.
• Generate data‑driven insights and recommendations for design, reliability, service engineering, and customer support teams.
• Conduct statistical analyses to evaluate data quality and completeness.
• Collaborate with engineering teams to support investigations and continuous improvement using enterprise data resources.
• Prepare technical documentation, presentations, and reports for technical and non‑technical audiences.

Skills

Data analytics

Machine learning

English communication

Statistical methods

Engineering data interpretation

Communication

Education

Bachelor's in STEM

Advanced degree (MS/PhD)

Tools

Python

NumPy

Pandas

PySpark

SQL

Tableau

Power BI

JIRA

Confluence

Job description

Job Overview

We are seeking a motivated Data Analytics Engineer with foundational knowledge in Mechanical Engineering and Machine Learning. In this role, you will analyze aircraft services and engineering datasets, uncover performance insights, and develop predictive models that support forecasting, field performance, and reliability initiatives.

Location & Employment

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

Key Responsibilities

• Analyze engineering and aircraft performance datasets to generate actionable insights for product performance and reliability.
• Perform data curation, cleaning, integration, and preparation for analytics, modeling, and machine learning workflows.
• Work with strain gauge, structural, thermal, and flight/aircraft data to extract features, identify trends, and detect anomalies or predictive indicators.
• Develop, train, and validate machine learning (ML) models (e.g., supervised learning, unsupervised learning, clustering, anomaly detection) for applications such as predictive maintenance, service interval estimation, and performance forecasting.
• Define validation methods, acceptance criteria, and performance metrics for analytical and predictive models.
• Generate data‑driven insights and recommendations for design, reliability, service engineering, and customer support teams.
• Conduct statistical analyses to evaluate the quality and completeness of engineering or enterprise data.
• Collaborate with engineering teams to support investigations and continuous improvement initiatives using enterprise data resources.
• Prepare technical documentation, presentations, and reports for both technical and non‑technical audiences.
• Occasionally travel domestically and/or internationally to support project requirements.

What You Will Learn

You will learn about our growing engineering team in Puerto Rico; what we do, who we support, and how we work. You will gain exposure to the technologies of today and tomorrow that are critical to maintaining world leadership in the aerospace industry, and you will discover why people find fulfillment working in this field.

Requirements

• Typically requires a degree in Science, Technology, Engineering or Mathematics (STEM) and 2 years prior relevant experience or an Advanced Degree in a related field.
• Demonstrated professional experience communicating in English (verbal and written).
• U.S. citizenship is required.
• Experience in data analytics workflows, statistical methods, and engineering data interpretation (internship/co‑op experience qualifies).
• Hands‑on experience with Python for data analysis (e.g., NumPy, Pandas, PySpark).
• Practical knowledge of machine learning concepts, with experience developing and validating models for prediction, classification, or anomaly detection.
• Foundational understanding of mechanical engineering principles (e.g., structural behavior, dynamics, thermal concepts) or familiarity with aircraft systems.
• Strong analytical and problem‑solving abilities, with the capability to communicate technical insights clearly to engineering and non‑technical stakeholders.
• Proficiency with Microsoft Office tools.

Preferred Qualifications

• Degree in Mechanical Engineering, Aerospace Engineering, or a closely related STEM field.
• Experience in aerospace, defense, or related industry.
• Familiarity with database tools and SQL for data extraction and manipulation.
• Exposure to data visualization tools (e.g., Tableau, Power BI).
• Experience with Agile methodologies and tools such as JIRA and Confluence.
• Exposure to digital thread concepts, PLM systems, or model‑based engineering workflows.
• Experience applying machine learning (ML) models to mechanical engineering or physical‑system datasets.

Benefits

• 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!

Equal Opportunity

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, 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.