Advances in Financial Machine Learning

None of the generic thought leadership books are particularly useful. I've noticed that the best way to keep relevant as an engineer is to ignore flavor of the day frameworks and tech but rather focus on the basics. For example, if you're working in financial modeling, one way to improve as an engineer to get better at the domain. Maybe "Advances in Financial Machine Learning" by Marcos López de Prado. You'd have to work through the math and pick up finance on the go (which I assume should be easier part). As for people doing cool stuff in Zig / Rust, what matters is the problem not the hammer they're using to solve it.

1. Inside the Black Box Introduction to quantitative finance and to learn what strategies are used by firms who are supposed to beat the market. 2. Advances in Financial Machine Learning Deep dive into ML techniques if you want to start making money from data and math.