Your first tasks would include:
⦁ Building an automated customer risk assessment system to help reduce manual effort and control overall risk
⦁ Building bet recommendation system to increase customer engagement
⦁ Identification and analysis of customer behavorial patterns in the context of sports betting.
⦁ Design and creation of automated customer risk assessment systems.
⦁ Creation of recommendation systems based on customer performance.
⦁ Support product development in mathematical aspects (for instance by creating a formula for a new betting feature).
⦁ Analysis of selected sports model and pricing performance, aiming to identify areas for improvement.
⦁ Play a challenging partner role within the team.
⦁ A solid understanding of the fundamentals of statistical prediction and probability theory including (but not limited to) an in-depth knowledge of regression and model fitting
⦁ Intellectual curiosity, creativity and confidence to try new approaches
⦁ Excellent problem solving and communication skills, including communication with non-technical partners
⦁ Programming experience, ideally in Python or R
⦁ Master’s qualifications in a quantitative field (mathematics/statistics/physics/etc), postgraduate/research experience (PhD/postdoc) are preferred.
⦁ Confidence to work with significant autonomy
⦁ Fluent English
⦁ Familiarity with Bayesian statistics, or an in-depth knowledge of generalized linear models (GLMs) would be a strong plus
⦁ Experience in a similar role
⦁ An interest in sports or competitive games
⦁ Quantitative research experience, possibly as part of a PhD or postdoc role
⦁ Strong Python and/or Java programming skills with exposure to data science
⦁ SQL skills
⦁ Prototyping experience
⦁ Kaggle profile
⦁ Familiarity to sports betting concepts
⦁ Experience with customer risk management