Makes value out of data and analysis them. Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc. Experience with common data science toolkits Good applied statistics skills, such as distributions, statistical testing, regression, etc. Good scripting and programming skills