
I’m Daniel Lindestad, with a background in analytical finance and computer engineering, focused on applied machine learning and decision-support systems. I enjoy working where technical systems meet real-world users: shaping product direction, clarifying tradeoffs, and turning complex models into something stakeholders can trust and act on. In FairWater, I focused on product, communication, and the story connecting the simulator, optimizer, and policy use case.