Key Responsibilities:
- Design and implement machine learning models for use cases such as customer segmentation, churn prediction, dynamic pricing, fraud detection, and recommendation systems.
- Collaborate with data engineers and analysts to build end-to-end ML pipelines using cloud-native tools (e.g., AWS SageMaker, Lambda, Step Functions).
- Work with large-scale structured and unstructured datasets from gaming systems, loyalty programs, CRM, and IoT devices.
- Monitor and maintain model performance in production, retraining and tuning as needed.
- Translate business problems into data science solutions and communicate results to stakeholders.
- Ensure compliance with data privacy and gaming regulations in all ML applications.
- Stay current with the latest ML research and tools, and evaluate their applicability to our business.

Required Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related field.
- Experience in machine learning or applied data science roles.
- Proficiency in Python and ML libraries such as scikit-learn, TensorFlow, PyTorch, or XGBoost.
- Experience with AWS ML services (e.g., SageMaker, Glue, Redshift, S3).
- Strong understanding of data preprocessing, feature engineering, and model evaluation.
- Familiarity with MLOps practices and tools for versioning, deployment, and monitoring.

Preferred Qualifications:
- Experience in the casino, gaming, or hospitality industry.
- Knowledge of real-time analytics, reinforcement learning, or deep learning.
- Experience with streaming data (e.g., Kinesis, Kafka) and big data platforms (e.g., Spark).
- AWS or ML-related certifications.