As the Data Science lead on a multi-disciplinary team at Sonic Tools USA, I spearheaded the development of a custom Return on Investment (ROI) calculator that quantifies the value of transitioning from standard industry tools to Sonic’s high-efficiency toolboxes. This tool is now embedded in Sonic’s customer engagement process to demonstrate projected cost savings and productivity improvements.

Our work began with a time-and-motion study across various technicians, comparing task durations between Sonic’s 209-piece and 322-piece carts and conventional toolsets. We categorized tasks by difficulty — Simple, Moderate, Complex, and Inventory — and measured real-world performance improvements, some exceeding 28%.

Leading the Data Science subteam, I:
• Coordinated data analysis strategy and validation
• Managed all communication between our team, company stakeholders, and faculty advisors
• Translated raw time data into usable business metrics, such as labor efficiency and payback periods
• Designed the core mathematical model for time saved, money saved, and ROI

We built the calculator in Calchub with a user-friendly WordPress frontend, allowing customers to input real data (e.g., team size, wage, hours, task mix) and receive an interactive breakdown of projected savings. To improve realism, I introduced a ternary input system to reflect companies’ unique task distributions, which dynamically affects ROI estimates.

Key features of the final tool:
• Data-driven ROI computation using empirical efficiency rates
• Custom investment recommendation logic
• Modular and scalable backend logic (Node.js-ready)
• Responsive UI integrated into Sonic’s live website

This project not only enhanced my skills in data modeling, applied business analytics, and frontend/backend integration, but also showcased my ability to lead technically and communicate across disciplines in a professional, client-facing environment.