Engineer II, Data Analytics & Machine Learning (Hybrid - Aguadilla, PR)
About The Position
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. A solid understanding of mechanical engineering fundamentals will help you interpret technical data and collaborate effectively with subject matter experts. This analytics-focused role works closely with engineering discipline owners, offering opportunities for professional growth and meaningful contributions to data driven reliability improvements. 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.
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, as only U.S. citizens are authorized to access information under this program/contract.
- 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.
Nice To Haves
- 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.
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.
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.
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
