Rigorous understanding of statistics and ability to discern appropriate statistical techniques to problem-solve.
Proficient in Python programming language and familiar with NumPy, Pandas, and Matplotlib libraries.
Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, etc., and their real-world advantages/drawbacks.
Ability to visualize and communicate the results (the ability to extract practical knowledge from raw data and storytelling based on the results).
Familiar to Git.
Bonus Skills:
Prior work experience in the financial industry.
Familiarity with deep learning and its frameworks.
