Speaker: Soups Ranjan

Financial Crime Risk @RevolutApp

Soups Ranjan heads Financial Crime Risk at Revolut, the fastest growing challenger bank in Europe. He leads the team in charge of preventing financial crime on Revolut’s platform using data science and machine learning. Soups has 14 years of experience applying machine learning to domains ranging from network security to advertising and cryptocurrencies. Prior to Revolut, Soups was the director of data science and risk at Coinbase, one of the largest cryptocurrency exchanges in the world. At Coinbase, Soups built many engineering teams from the ground up including data, risk and identity. Soups is the co-founder of RiskSalon.org, a roundtable forum for risk professionals in San Francisco and Seattle to share ideas on stopping financial crime. Soups holds a PhD in ECE focused on network security from Rice University. Soups currently lives in Berkeley with his family.

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2019 Tracks

  • Sequential Data: Natural Language, Time Series, and Sound

    Techniques, practices, and approaches around time series and sequential data. Expect topics including image recognition, NLP/NLU, preprocess, & crunching of related algorithms.

  • ML in Action

    Applied track demonstrating how to train, score, and handle common machine learning use cases, including heavy concentration in the space of security and fraud

  • Deep Learning in Practice

    Deep learning use cases around edge computing, deep learning for search, explainability, fairness, and perception.