High-Impact Data Automation for Magna International

(R&D Internship, Magna International, Research and Development Team for Ferrari's first SUV)

Data/Software Engineer Sept. 2021 - Aug 2022

Context

I joined Magna’s R&D group working on a prototype component for the Ferrari SUV. Testing the component's electrical and mechanical performance relied on slow, manual Excel workflows. Each analysis could take two full workdays, and accuracy depended on engineers visually inspecting graphs.

Problem

The process was both confidential and critical to get right, since results were shared directly with Ferrari. Because of the stakes, the team was hesitant to change how data was handled.

Solution

I proposed automating the analysis and built a small proof of concept to earn trust. Once approved, I:

• Created custom algorithms for every performance test, translating expert visual checks into repeatable logic.
• Developed an automated pipeline that processed raw data and produced precise reports in under 10 seconds, replacing a two-day manual effort.
• Delivered results that were more accurate and consistent than the traditional workflow.

Interface for Engineers

To make the tool usable for a non-software team, I designed my first interactive user interface. It enabled engineers to:

• Run standard analyses instantly.
• Configure and execute custom tests.
• Explore results through clear, dynamic graphs.

Impact

The software became part of the team’s standard process, saving days of work and improving confidence in results. Managers noted they had never seen an intern deliver such a solution, especially for high-stakes, sensitive data.

Key Takeaways

By questioning assumptions and backing ideas with prototypes, I built a system that combined algorithm design, automation, and user experience. It transformed how a flagship automotive project evaluated its prototypes and showed how much value strong engineering initiative can create.