Data Scientist

• Learn how predictive models look like in a betting context and build models on your own.
• Support the team in maintaining the codebase.
• Analyze/evaluate/optimize existing predictive models as model co-owner.
• Research new methods for future applications., * A collaborative environment with colleagues from all over the world (Engineering offices in Europe, Asia and US) including various social events and teambuilding.
• Ability to shape your own workday and career via a clearly defined professional and personal development plan.
• Opportunity to develop yourself within an inspiring and fast-growing company with our Career framework possibilities.
• Vibrant and inclusive community, including Women in Tech and Pride groups which welcome all participants.
• Global Employee Assistance Programme.
• Calm and Reulay app (managing stress, maintaining focus, improving sleep, building resilience).
• Online training videos.
• Flexible working hours.

• Master’s degree or equivalent/higher qualification in one of the following disciplines: Data Science, Statistics, Mathematics, Software Engineering or a closely related field.
• Experienced in predictive modelling, with a deep understanding of data analysis and modelling techniques such as GLMs, Time-Series Analysis, Bayesian Statistics, MCMC, neural networks, etc.
• Very strong skills in R or python.
• Advanced coding and analytical skills.
• Strong communication skills, fluency in English.
• Creative thinking, keen to further refine systems and processes.
• Highly self-motivated, leading by example and enthusiasm.
• Being a team player, with the ability to work with new teams immediately.
• Strong interpersonal skills.

Preferred:

• Experience in object-oriented programming, preferably Java.
• Experience with Gitlab, Jira & Confluence.
• Experience with SQL.

Reporting to the Head of Quants you will be working closely with your colleagues in Quants but also various product owners, developers and traders company wide. Our department is responsible for creating predictive models for both pre-match and in-play betting markets in various sports. This typically requires cleaning up, visualizing, analyzing and interpreting relevant data, as well as implementing the created models in Java and testing them. Publishing and maintaining these Java libraries is also one of our responsibilities. Furthermore, we are providing various data analysis or generally math related tasks on demand.