Staff Data Scientist - Fraud & Risk

Tech Stack

Responsibilities

• Design, develop, and implement advanced deep learning models (transformers, CNNs/RNNs, graph learning) for fraud and risk challenges.
• Build and optimize models using diverse input data types including tabular data, natural language, point clouds, and images.
• Lead the end-to-end machine learning lifecycle: data exploration, feature engineering, model training, evaluation, deployment, and monitoring.
• Take ownership of project outcomes, data quality, and delivery timelines, proactively resolving challenges.
• Mentor and share knowledge with peers and junior data scientists, fostering a culture of experimentation and continuous learning.

Culture

Requirements