Design, develop, and implement deep learning models (transformers, CNNs, LSTMs) for fraud and risk.
Build models using tabular data, natural language, point clouds, and images.
Own assigned tasks with minimal supervision to meet project goals.
Participate in the ML lifecycle: data exploration, feature engineering, model training, evaluation, and deployment.
Collaborate across teams to share knowledge and drive results.
Make routine technical decisions and contribute to functional objectives.
Stay current with AI/ML advances and apply innovative approaches.
Communicate results clearly to technical and non-technical audiences.

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