Python Machine Learning for Online Trading

Hello, I am looking for a Machine Learning expert to develop a framework for creating online trading strategies (Futures, Forex, Equities, Crypto Currencies,...). All strategies need to be in a human readable form f.e. IF RSI(14) <30 AND close(1) > Yesterdays HI and Close(1) > Moving Average(20) THEN Buy this bar on close. I dont want to implement a Neural Net where the output is only some coefficients but as mentioned above the output should be in readable form. The Machine Learning Algorithms I wish to deploy would be those that produce human readable strategies (i.e. Grammatical Evolution, Genetic Algorithms, Decision Tree,...). In order to find useful features, feature importance must be first analyzed. In this step I dont mind using algorithms which are not in human readable form. I would like to use Scitkit learn RandomForest, KNN, DecisionTrees and XGBoost and SVMs. Most favored to analyze feature importance would be RandomForest and XGBoost. In this step, I wish to see a sorted table where the most important features are on the top and least important are on the bottom. In the next step, you will use a certain percent of the most important features. Here you develop the trading strategies by using Grammatical Evolution, Genetic Algorithms and Decision Trees. a few important things: - - features need to be able to be combined - Whenever possible, use Scikit Learn - the data must be split up into train, test and validation sets (40,40,20) -since i am a beginner in Machine Learning a bit of coaching will be needed. - you must be an expert in machine learning and should have done multiple projects. Ideally you have experience in Financial markets also or at least in Time-series analysis.