data scientist

The project focuses on enhancing customer safety and regulatory compliance through predictive risk-scoring models for Anti-Money Laundering (AML) and Safer Gambling risk mitigation.

• Design, evaluate, and iteratively refine predictive models targeting AML and Safer Gambling risk indicators;
• Conduct exploratory data analysis and targeted investigations to identify behavioral anomalies and emerging risk patterns;
• Partner with compliance and operational risk teams to translate risk domain insights into practical model features;
• Communicate analytical methodologies, model evaluation results, and strategic insights to non-technical stakeholders.

• 5+ Years of professional experience in a Data Scientist role;
• Strong proficiency in Python and SQL for complex data extraction, feature engineering, and statistical modeling;
• Practical expertise in building and evaluating standard statistical and machine learning models, such as XGBoost and Linear/Logistic Regression;
• Strong analytical problem-solving skills and experience with model evaluation metrics and data-driven investigations;
• Effective verbal and written communication skills, including the ability to explain complex analytical concepts clearly;
• Nice to have: prior experience in online gaming, familiarity with Anti-Money Laundering (AML) regulations or Responsible/Safer Gambling frameworks, basic conceptual understanding of model deployment pipelines (hands-on engineering deployment expertise is not required).

• No conditions specified