Data Scientist II, Fraud & Risk

Tech Stack

Responsibilities

• Design, develop, and implement advanced deep learning models, including transformers, CNNs, and LSTMs, to address complex fraud and risk challenges.
• Build and optimize models using a variety of input data types, including tabular data, natural language, point clouds, and images.
• Participate in all stages of the machine learning lifecycle: data exploration, feature engineering, model training, evaluation, and deployment.
• Collaborate effectively across teams, sharing knowledge and learning from diverse perspectives to drive results.
• Communicate results and insights clearly to both technical and non-technical audiences.

Benefits

• Equity
• Health Insurance

Culture

Requirements