Machine Learning Engineer

• Understanding business objectives and developing models that help to identify and prevent credential stuffing, ATO (account takeover) and other fraud behaviors, along with metrics to track the progress.
• Exploring and visualizing data to gain an understanding of the problems, then identifying differences in data distribution and selecting the suitable ML algorithms.
• Apply machine learning, statistics or data mining to help to be efficient in every aspects of identity security.
• Develop scalable and efficient methods for large scale data analysis and model development.
• Defining data augmentation pipelines, training models and tuning their hyperparameters, deploying models to production, monitoring & evaluating the performance of ML models.
• Collaborate with developers, program managers, and product managers in an open, creative environment.

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