We are looking for a machine learning engineer who will be responsible for developing algorithms that will be the basis of our mathematical models used to understand and automate the trading process of sports betting markets. Candidate must have strong background in Machine Learning, Statistics, and Algorithm Development.
Essential Job Functions / Main Duties & Responsibilities:
Perform industrial research by developing math models and algorithms to be used in automated
trading applications in the sports betting domain.
Evaluate state-of-the-art statistical modelling and Machine Learning approaches using large
amounts of historical data
Analyze, Visualize and Model large datasets using R and Python.
Acquire, Clean, and Transform data using R and Python.
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
Flexibility and adaptability to business requirements and priority changes.
Knowledge & Experience:
3+ years of relevant experience with statistical computing in R or Python.
3+ years of experience with Machine Learning algorithms and Probabilistic Modelling.
Strong background in statistics, preferably Bayesian Statistics.
Experience with Bayesian Inference using Statistical Languages for MCMC such as Stan, JAGS,
WinBugs is a big plus.
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
Experience with SQL and SQL Server
Experience with .NET Framework and C# is preferable
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.
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