Position: Data Scientist / Sports Quantitative Analyst
Company: EveryMatrix
Experience required: 1y
Category: Data Science
English level: intermediate
Published: 2021-10-01T00:00:00+03:00

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

Main responsibilities:
⦁    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.

What will make you successful in the role:
⦁    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

Skills that will help you stand out:
⦁    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