Lean Systems

The Context

Lean Systems was a Techstars NYC '17 startup applying operations research to transportation and aviation. I joined in April 2017, right after finishing my PhD at McGill. The company was early stage, and I was responsible for designing and implementing the optimization algorithms that were the core of the product.

What I Built

I designed vehicle-routing algorithms for a ground transportation client, solving the classic problem of getting the right vehicles to the right places at the right times while minimizing cost. I also built maintenance scheduling models for business aviation clients, optimizing when and where to service aircraft to maximize fleet availability.

Beyond the algorithms, I developed interactive Python/JS web applications that let clients visualize their fleet operations data. These tools turned abstract optimization results into something a fleet manager could understand and act on.

I also contributed to the architecture and implementation of the core optimization engine that powered all of the company's products.

What I Learned

This was where I learned to bridge the gap between mathematical optimization and real-world operations. A routing algorithm that produces a theoretically optimal solution is useless if the driver cannot follow it. The visualization tools I built were as important as the algorithms themselves because they made the results actionable.

Working at a Techstars startup also gave me my first taste of the startup environment: small team, limited resources, ship fast, learn faster. That experience informed everything I did later at Grownomic.