Advanced Diagnostics Integration Intern

About Rivian

Rivian is on a mission to keep the world adventurous forever. This goes for the emissions-free Electric Adventure Vehicles we build, and the curious, courageous souls we seek to attract.  As a company, we constantly challenge what’s possible, never simply accepting what has always been done. We reframe old problems, seek new solutions and operate comfortably in areas that are unknown. Our backgrounds are diverse, but our team shares a love of the outdoors and a desire to protect it for future generations.

About the role

Rivian internships are experiences optimized for student candidates. To be eligible, you must be an undergraduate or graduate student in an accredited program during the internship term with an expected graduation date between December 2026 through May 2028. Rivian’s Internship Program requires active student enrollment. Information regarding your expected degree completion date is collected solely to verify eligibility and determine your availability for future full-time opportunities. Rivian is an equal opportunity employer and does not use graduation dates to determine the age of applicants or as a basis for discriminatory hiring decisions.  

If you are not pursuing a degree, please see our full time positions on our Rivian careers site. 

Note that if your university has specific requirements for internship programs, it is your responsibility to fulfill those requirements. 

The Data Analytics Intern will help develop data analysis tools and dashboards for advanced vehicle energy management systems using cloud data. This work enables the early detection and tracking of field issues as vehicle production volumes scale. In this role, you will analyze diagnostic fault codes, network logs, high-resolution hardware data, and general system logs to identify performance or system‑level issues related to charging and power conversion. You will build dashboards and automated alerts that highlight fault frequency, correlate issues with software versions and manufacturing dates, and surface relevant data signals for root‑cause analysis. Ultimately, your work will significantly reduce the time required to pinpoint the exact conditions under which issues occur, directly improving vehicle reliability and customer satisfaction for core functions like charging and power management. 

Responsibilities

• Dashboard Development: Design and build interactive dashboards that provide an overview of system diagnostic faults, including the specific operational state of the module when a fault was triggered.
• Data Integration: Integrate high-resolution data captures so they can be viewed and analyzed directly within the dashboard for specific faults of interest.
• Automated Triaging: Develop an automated triaging system to categorize and generate internal tracking tickets based on vehicle identifiers, timestamps, and active software releases.
• Fleet Monitoring: Monitor critical performance parameters across the entire vehicle fleet to establish and track key performance metrics.
• Alerting Systems: Create automated chat-bot notifications (e.g., Slack) for newly detected system issues or fault codes, including direct links to the relevant dashboards to support rapid engineering triage.

Qualifications

• Must be currently pursuing a bachelors, masters, or PhD degree at the University of Illinois Urbana Champaign
• Actively pursuing a degree or one closely related in Data Science
• Strong background in data analysis and coding (Python or similar programming languages)
• Ability to work with large datasets generated from vehicle systems, including DTCs, PCAP logs, high-resolution oscilloscope data, and lofi logs, to identify patterns and issues.
• Experience building or using dashboards/visualization tools to monitor system performance and fault behavior.
• Strong analytical and problem‑solving skills, with the ability to support software and controls engineers in root‑causing field issues.
• Basic background in electrical circuits, preferred.
• Experience working with cloud based platforms and automated alerting/notification tools preferred

To apply, please use this link: https://go.researchpark.illinois.edu/AdvancedDiagnosticsIntegration_Rivian