Дата публикации 04.02.19

Scientific Data Analyst Intern



  • setting up data flows and defining data models across multiple components;
  • prototyping intelligent agent functionality in a multi-layer ecosystem (various AWS services, RabbitMQ, Spring framework, Splunk, MLTK, etc.);
  • researching applicability of cutting edge AI techniques to our use cases (Agent Based Modeling, Deep Learning, Hierarchical Temporal Memory, etc.);
  • collecting and processing large volumes of financial market related data;
  • constructing machine learning pipelines;
  • conducting experiments and analyzing results;
  • describing your work in blog posts and scientific papers.


  • proactive self-starters who can work with little oversight;
  • fluent English. We are an international team and most of the business is conducted in English. You need to be able to speak and write fluently;
  • background in Mathematics, Neuroscience, Finance, Data or other sciences;
  • proficiency in Java, Python, or other relevant languages and libraries;
  • general understanding statistical methods of data analysis, machine learning, neural networks, etc;
  • experience in data analysis, programming, blockchain technologies, finance, securities trading, cryptocurrency, or any other related area is a big plus;
  • we are always happy to consider part-time and student applications.


  • you'll be a part of a small team of computer engineers, security experts, scientists, mathematicians, and finance experts from the US, Europe, and Russia;
  • you'll get to work on cutting edge technologies in Machine Learning, Data Science, blockchain, and finance;
  • we have a clear and open development process on GitLab. You'll see the result of your work with zero red tape slowing things down;
  • most of our code is open source and your contribution will be properly attributed;
  • we have great hang-out spots/offices in downtown Washington DC, Paris, and Saint Petersburg, but we are open to part-time and remote applicants.

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