Data Scientist at Sporty Group

We consistently top the charts as one of if not the most used Sports Betting website in the countries we operate in. With millions of weekly active users, we strive to be the best in industry for our users. As a Data Scientist at Sporty, you will play a vital role in developing innovative data science solutions and machine learning models to drive business impact. Working closely with our Trading, Product, and Tech teams, you will leverage your expertise to tackle a wide range of business challenges, translating them into supervised and/or unsupervised learning problems.

Who We Are

Sporty Group is a consumer internet and technology business with an unrivalled sports media, gaming, social and fintech platform which serves millions of daily active users across the globe via technology and operations hubs across more than 10 countries and 3 continents. The recipe for our success is to discover intelligent and energetic people, who are passionate about our products and serving our users, and attract and retain them with a dynamic and flexible work life which empowers them to create value and rewards them generously based upon their contribution. We have already built a capable and proven team of 300+ high achievers from a diverse set of backgrounds and we are looking for more talented individuals to drive further growth and contribute to the innovation, creativity and hard work that currently serves our users further via their grit and innovation.

Responsibilities

• Create data science solutions to address a variety of business challenges that can be translated to supervised and/or unsupervised learning problems using statistical and machine learning models.
• Participate in monitoring and evaluation of performance of existing models.
• Develop advanced quantitative models and concepts, such as LTV models, churn models, and recommendation engines.
• Collaborate with global teams of developers, traders and product developers to better understand business requirements and deliver end product to the clients.
• Implement and test the researched fixed income models using the risk research data liabilities and probabilities calculations.

Requirements

• Ability to come up with sound research designs and make methodological choices to address business problems with appropriate statistical and machine learning models.
• 3+ years of experience as a data scientist, quantitative researcher, quantitative analyst or another relevant role.
• Degree in Applied Mathematics, Computer Science, Financial Engineering, Technology or Engineering.
• Knowledge of probability theory, inferential statistics, machine learning, Bayesian statistics, linear algebra, and numerical methods.
• Experience with statistical and machine learning models, such as regression-based models (e.g., logistic regression, linear regression, negative binomial regression), tree-based models (e.g., random forests), support vector machines, PCA, clustering models, matrix factorization, deep learning, etc.
• Experience using statistical and machine learning models to contribute to company growth efforts, impacting revenue and other key business outcomes.
• Advanced understanding of Python and the machine learning ecosystem in Python (Numpy, Pandas, Scikit-learn, LightGBM, PyTorch).
• Knowledge of SQL and experience with relational databases.
• Agile, action-oriented.

Nice to have

• Experience working in cloud platforms (AWS, GCP, Microsoft Azure).
• Relevant knowledge or experience in the gaming industry.

Working at Sporty

The top-down mentality at Sporty is high performance based, meaning we trust you to do your job with an emphasis on support to help you achieve, grow and de-block any issues when they’re in your way. Generally employees can choose their own hours, as long as they are collaborating and doing stand-ups etc. The emphasis is really on results. As we are a highly structured and established company we are able to offer the security and support of a global business with the allure of a startup environment. Sporty is independently managed and financed, meaning we don’t have arbitrary shareholder or VC targets to cater to. We literally build, spend and make decisions based on the ethos of building THE best platform of its kind. We are truly a tech company to the core and take excellent care of our Team Members.