Описание
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.
Задачи
•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
Требования
•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)
Условия
No conditions specified
