Soukaina

· Collecting, analyzing, and exploring booking trends. · Developing advanced algorithms to predict booking curves. · Hyperparameter tuning and validation/testing metrics. · Using MLflow to manage the model lifecycle: experiments, archiving parameters, metrics, etc. · Deploying Machine Learning models and algorithms in production. · Python packaging of Machine Learning models with a focus on clean code and modularity. · Implementing integrated unit tests in CI/CD pipelines to ensure solution reliability. · Optimizing Spark job performance for faster and more efficient execution. · Mentoring junior data scientists