Strong understanding of statistical methods, ML algorithms, and deep learning architectures. Must be proficient in Python and have experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, or Keras. Must be familiar with cloud-based platforms and services, such as AWS, GCP, or Azure. Need to have experience with natural language processing (NLP) techniques and tools, such as SpaCy, NLTK, or Hugging Face. Knowledge of model interpretability and fairness frameworks (SHAP, LIME, Fairlearn) and responsible AI principles