The role focuses on turning large volumes of ship maintenance, logistics, and readiness data into predictive insights and decision-support tools that improve fleet availability, reduce unplanned maintenance, and accelerate work-package planning. • Develop end-to-end ML pipelines — data ingestion, feature engineering, training, evaluation, deployment, and monitoring — using Python and modern ML frameworks (PyTorch, TensorFlow, scikit-learn, Hugging Face).