Collecting (parsing) and preliminary preprocessing of data
Creating algorithms to predict the outcomes of sports events.
Implementing these models into the existing system.
Developing new models and updating existing ones.
At least 3 years of experience as a Data Scientist
Proficiency in Python (Pandas, NumPy, Selenium, Scikit-Learn, Plotly, etc.)
Knowledge of fundamental machine learning techniques (such as regression, clustering, decision trees, and deep learning) and practical experience in their application
Strong grasp of probability theory, including normal distribution, Poisson distribution, combinatorics, and Bayesian methods, and the ability to assess the statistical significance of results
Understanding of data cleaning, transformation, and normalization methods, with practical skills in applying them to model development