Competitive Balance Analytics

Position: Quantitative Modeler - US Sporting Events Location: Remote (US) Looking for a talented and highly motivated Quantitative Modeler for a unique and exciting opportunity to work with a small team to accurately predict the outcomes of future US sporting events. Candidate must have a strong understanding the wagering markets involving these events.  Candidate should have hands-on experience with statistical modeling.  Ideal candidates will also have experience in traditional data science (analyzing data) and more modern data science (AI, deep learning). Candidates must be capable of working in a remote environment. Required Qualifications:  Python (scripting, numpy, scipy, matplotlib, scikit-learn, jupyter notebooks) Experience with machine learning algorithms, such as neural networks/deep learning, SVM, XGBoost, Random Forest, generalized linear models, etc. Understanding of Sports Wagering Markets Experience with Amazon Web Services (EC2, S3, SageMaker,...