After 4 years in the Software Engineering industry, I realized my path was too mondy. I would always deal with Data Science related projects. Working in a small company, enterprise and a startup shaped my industry perspective but nothing was quite satisfying. My good old passion for Algorithmic Trading would never leave me. I wanted something else, so Moey decided to quit my Data Science career and pursue day trading for a living. We have seen Machine Learning applications. Most of the paper trading tests will be awesome and will fail in real trading because they over-fit. You will fight it with cross validation and cherry pick the best models that performed best on out of sample, thinking you are safe, in a way adding bias and leaking data. This is not the way to do. Avoid over-fitting by carefully averaging and evaluating on different assets, time frames or periods.