Data Science team responsible for the modeling, implementation and monitoring of ML fraud prevention solutions. Researching large data sets from various sources and characterize new research and analysis tools to optimize and improve risk engine performance.

Research and development of machine learning/data science algorithms for RSA eCommerce and Online Banking products.

Fortscale (Acquired) is redefining behavioral analytics, with the industry’s first embeddable engine, making behavioral analytics available for everyone. Fortscale automates the delivery and use of behavioral analytics throughout the security infrastructure, embedding it within the native operations of security devices, so it can be used to quickly pinpoint risks, improve decision-making and strengthen security. When integrated, Fortscale processes the data collected by the device, using predictive, big data analytics and advanced machine learning, to autonomously model behaviors and quickly and accurately identify anomalous, high-risk activity. Developing models in the domain of UBA (anomalous user behaviour), with emphasis on statistics and unsupervised machine learning algorithms, from research to production.

Machine Learning
Supervised Learning Unsupervised Learning
Java Python R