Position: Head of Quantitative Analysis
Company: EveryMatrix
Category: Data Science
Experience required: 5y
English level: upper
Published: 2020-10-01T00:00:00+03:00

Responsibilities:

· Design, build and maintain derivative pricing data models, live and pre-live, across a broad range of sports;

· Improve the Risk Management model by implementing new numeric/quantitative techniques;

· Analyze business trends to identify scope for future product development;

· Provide reporting and performance monitoring of our products;

· Define and implement strategy for collecting, reporting and analyzing data in order to improve decisions relating to our sportsbook;

· Supporting other teams who are integrating or testing the sports models.

· Ensure data quality and availability;

· Ensure distribution of knowledge and be available to team members to assist with any issues they may have.

· Learn the touchpoints where changes within a model may have an impact on other business areas.

· Understand, identify and mitigate any risks in delivery of work.


Requirements:

· Minimum 3 years experience in a similar role within the online sports betting industry;

· Extensive experience with odds models from a leading sportsbook;

· A master’s degree in computer science, mathematics, statistics or a related field is required (PhD in Mathematics or Statistics would be considered a huge plus);

· Applied math / statistics in other industries (e.g. Finance) is an asset;

· Excellent understanding of probability and statistics;

· Excellent knowledge of BI tools, ETL, Data structure, Data analysis;

· Experience with analytical platform such as: Matlab, R, Python etc;

· Excellent SQL skills;

· Experienced in sports data mining and sports analytics;

· Development experience in one of the languages: C, C++, #C, JAVA would be a plus;

· Proficiency in English.

· Strong leadership skills with ability to achieve results by working through others;

· Ability to understand business challenges and formalise them into appropriate analytics and modelling requirements .

· Delivery and results focused with a problem solving attitude;

· Very good at organizing and prioritizing tasks