As an Algorithm Developer , candidate will be responsible for developing algorithms that will be the basis of our mathematical models for our understanding of sports betting markets, which will be used for automation. The candidate MUST have a strong background in Machine Learning and Algorithm Development experience.
Essential Job Functions / Main Duties & Responsibilities:
- Perform industrial research by developing math models and algorithms to be used in automated trading applications
- Evaluating state-of-the-art statistical modelling and Machine Learning approaches using large amounts of historical data
- Data Analysis, Visualization and Modelling with large datasets
- Data Acquisition, Cleaning, and Transformation
- Deploy models using .NET framework (C#) to production environment and provide support
Skills & Qualifications:
- Degree or Diploma in Computer Science, Software Engineering, Computational Statistics or equivalent degree or experience
- MS or PHD in Computer Science, specializing in Machine Learning is desirable
- Strong analytical, conceptual, and problem-solving abilities with attention to detail
- Ability to multi-task and manage multiple assignments in a fast-paced environment.
- Strong written and oral communication skills
- Initiative to work independently, but also able to work effectively with team members in different locations
- Flexibility and adaptability to business requirements and priority changes
Knowledge & Experience:
- 3+ years of relevant experience with R or Python (NumPy, SciPy, Pandas, etc)
- 2+ years of relevant experience as Software Developer, preferably using Microsoft .NET Framework (C# or VB.NET)
- Strong background in statistics
- Experience with Machine Learning algorithms and Probabilistic Models
- Experience using cloud computing platforms such as EC2 (AWS)
- Domain experience in on-line gaming and entertainment industry, Financial Markets (such as Stock Exchange, Options, Bonds, ForEx, etc), or other types of 2-sided markets is a plus
- SQL and SQL Server
- Experience with modern R packages and technologies such as dplyr, tidyR, data.table, shinyR
- Experience with Neural Networks or Deep Learning on large problems is a PLUS
- Hadoop, MapReduce or High Performance Computing is a plus