Aerospace Engine Data & ML Internship

RTX; Town of Florida (NY); On-site; USD 37,000 - 82,000; Full time

Benefits offered by this job

Relocation Eligibility

Job summary

RTX is offering an internship in its engine validation analytics group. You will develop, implement, and maintain predictive models to forecast risk factors and apply statistical methods to engine datasets.

You will design dashboards to communicate insights and contribute to knowledge assets within RTX’s ESW and training programs. Learned students will gain hands-on experience working with engineers on jet engine validation, with on-site responsibilities and collaboration across teams.

Qualifications

• Must be pursuing a Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field and actively enrolled through the completion of the internship/co-op session.

Responsibilities

• Develop, implement, and maintain predictive models to forecast risk factors in support of engine validation planning.
• Apply statistical models to identify patterns, trends, and anomalies in engine validation datasets to extract actionable insights.
• Design and implement data visualization dashboards and reports to communicate findings effectively.
• Develop and publish new knowledge assets within EKS (ESW, K-Packs, GB, training, etc.)
• Communicate results and insights to technical and non-technical audiences in a clear and concise manner.

Skills

Python

SQL

Data analysis

Machine learning

Soft skills

Education

Bachelor's or Master's in CS/Engineering/Math

Tools

Relational databases

Job description

RTX is offering an internship in its engine validation analytics group. You will develop, implement, and maintain predictive models to forecast risk factors and apply statistical methods to engine datasets.

You will design dashboards to communicate insights and contribute to knowledge assets within RTX’s ESW and training programs. Learned students will gain hands-on experience working with engineers on jet engine validation, with on-site responsibilities and collaboration across teams.