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RavenPack Presents at J.P Morgan European Machine Learning Conference

RavenPack's Data Science expert is set to present and host a hands-on workshop at this years J.P Morgan Annual Machine Learning Conference in Paris. You can request access to his workshop materials.

RavenPack's Senior Data Scientist, Marko Kangrga, will participate on an expert panel discussing machine learning in the financial markets and trade ideas. The afternoon session will include a hands-on training session with practical examples on using big data and machine learning in a portfolio management context.

Panel Topic

How to use Machine Learning in Financial Markets? Trade Ideas and Big Data Panel

Panelists

  • Marko Kangrga, Senior Data Scientist – RavenPack
  • Bryan Yates, GM and Director of Sales – Orbital Insights
  • Alice Froidevaux, Data Scientist – QuantCube

Workshop Topic

Machine Learning with Practical Examples (Workshop)

This tutorial takes an in-depth look at natural language processing and machine learning techniques with applications in finance.

Access the workshop materials >

RavenPack Presenter: Marko Kangrga, Senior Data Scientist

Marko Kangrga is a Senior Data Scientist and the head of Fundamental Research at RavenPack with over 10 years of experience in the finance industry. He focuses on exploring novel approaches and techniques for combining fundamental drivers with big data quantitative frameworks to identify alpha opportunities from a wide universe of securities across multiple asset classes. Previously, as the head trader/investment analyst at a discretionary, event-driven hedge fund, he was responsible for macro research, idea generation and risk management. Marko has experience in utilizing quantitative methods in portfolio construction, developing hedging strategies and trading structured derivative instruments. He earned a B.S. degree in Finance, summa cum laude, with a minor in Computer Science from the University of Evansville in 2008.

When:
July 9, 2019

Where
14 Place Vendôme
75001, Paris, France

Request Event Materials

Request Event Materials

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