We are innovating the sports betting industry and aggressively expanding our cutting-edge Data Science Team. You will help design and build Machine Learning Algorithms that will be used by sports betting institutions to maximize profits and efficiently manage risk.
- Apply statistical techniques to analyze data and engineer relevant signals for sports markets pricing.
- Implement baseline Machine Learning-based pricing models, and improve upon them iteratively
- Learn and implement cutting-edge Machine Learning Algorithms to improve pricing accuracy
- Write production code to productize any Algorithms designed, ensuring they run in an online real-time fashion
- Apply statistics to and develop algorithms in problem spaces beyond pricing markets, such as user tailoring, determining betting limits, and managing risk
- Collaborate with management to align Algorithm Development with customer needs, business needs, and data science/risk engine vision
- Provide recommendations on Algorithms and problem spaces to explore as you work with and analyze data
- Write hardware-conscious, parallelized code to help productize predictive models
- Code efficient data stores & structures to store information at all levels of the memory hierarchy
- Collate data from a multitude of sources into efficient systems
- Strong interest in sports, the sports markets, and/or the betting markets. (sports analytics experience a plus)
- Degree (BS, Masters, PhD) in statistics, mathematics, or related quantitative field.
- Strong understanding of programming and computer science fundamentals
- Experience with low-level programming languages like C or Rust desired.
- Strong knowledge of statistics, AI/Machine Learning Algorithms, and Pattern Recognition techniques.
- Experience in productizing Algorithms, and improving efficiency/runtime
- Understanding of Python, SQL, R, or related data processing languages.
- Experience with graph algorithms and graph databases is a major plus
The interview process will be as follows:
- Math Test will be sent via email
- Technical Interview (phone or video)
- 2nd Assessment
- Onsite Interview