Qorvo is hiring a Data Engineering Intern for its High Performance Analog business group. The intern will analyze datasets, develop and evaluate machine learning models, engineer data features, and communicate findings while collaborating on moving promising models toward production.
Explore and analyze large, complex datasets to surface trends, anomalies, and actionable insights
Build, train, and validate machine learning models to support forecasting, classification, and optimization use cases
Engineer features from structured and unstructured data sources using Python and Spark on AWS
Design and evaluate experiments, applying statistical methods to assess significance and model performance
Communicate findings through clear visualizations, written summaries, and presentations to technical and non-technical audiences
Partner with engineers and analysts to move promising models from prototype toward production
Qualification
Required
Qorvo's Internship Program is designed for college students currently enrolled in an accredited Bachelor's, Master's, or PhD program
Currently pursuing a BS, MS, or PhD in Data Science, Computer Science, Statistics, Applied Math, or related field
Minimum GPA of 3.0
Proficiency in Python, including common data science libraries (pandas, scikit-learn, NumPy)
Coursework or hands-on experience in statistics, machine learning, or experimental design
Familiarity with SQL and Git
Strong organization skills and attention to detail
This position is not eligible for visa sponsorship by the Company
Preferred
exposure to Spark or cloud platforms is a plus
Benefits
Real work experience
Exposure to upper management
The opportunity to pursue full-time opportunities, as available
Challenging, skill-building assignments
Mentoring and coaching from industry experts
Launch & Learns and other learning opportunities
Collaborative team-based work environment
Networking and social events
Final presentation to business leaders
Qorvo is now a part of Skyworks®, a global leader in high-performance RF, precision timing, power management and mixed-signal solutions that power the intelligent, connected world.