We are looking for an enthusiastic junior to mid-level data scientist to join our dynamic and growing team at LeoVegas. The ideal candidate will have an open-minded attitude and be eager to learn. You will get the opportunity to work hands-on in the entire lifecycle of putting machine learning based applications in production.
Our team is responsible for providing the entire organisation, including all brands and markets, with algorithms for decision-making support, product personalization, and optimization and automation of business processes. Our project portfolio is diverse and constantly growing. Examples include churn prediction, lifetime-value prediction, player risk assessment models (responsible gaming), money laundering detection, and recommender systems to name a few.
Our data science team is not focused on reporting; we actively develop and deploy models into production that directly serve and enhance the entire organisation.

ESSENTIAL SKILLS

• 2+ years of experience in a similar role
• Understanding of fundamental concepts in statistics and machine learning
• Experience in apply machine learning, either in academia or industry
• Proficiency in programming languages such as Python or R.
• Experience with SQL
• Basic understanding of Git

WHO WE ARE

At the core of LeoVegas Group is Team Leo. Our culture is our foundation and is what enables us to innovate, build, and lead as we trailblaze our way through the igaming industry. We’re a team of over 1800 innovators, initiators, and groundbreakers working in a fast-paced and agile environment across 16 offices worldwide.

• Interpret stakeholder requirements to develop, implement, and fine-tune machine learning models that address their specific needs and business objectives.
• Improve and maintain existing machine learning models to enhance their performance, accuracy, and efficiency over time as well as following new regulations.
• Collaborate cross-functionally with various teams, including product, engineering, and business, to ensure seamless integration and alignment of machine learning solutions with overall company goals.
• Analyse and transform data using SQL to prepare datasets for machine learning model development and ensure data integrity and accuracy.
• Conduct A/B testing and other experiments to evaluate the effectiveness of new features and promotions.
• Collaborate with external parties to enable outsourced ML based applications.
• Perform advanced analysis on large and complex datasets to extract actionable insights and inform the business to make informed decisions