Machine Learning Research Scientist - Text Analytics

Careers at Bloomberg

New York, NY

Posted Jun 18, 2018 - Requisition No. 67707

Bloomberg’s core product, the Terminal, is a must-have for the most influential people in finance. In addition to being the second largest producer of news in the world, Bloomberg ingests more than 1.5 million news stories per day from more than 120,000 different sources to help our clients stay in the know. This data would be unmanageable without our help. News stories move markets. We build machines that understand them.

Machine Learning Text Analytics team works on extracting actionable signals from text of news and social media. We build systems that help compute market sentiment, analytics around news publication and news consumption and content novelty. Clients all over the world use our analytics on a daily basis to make critical financial decisions. We solve interesting challenges in the areas of supervised and unsupervised machine learning, text classification and NLP.

We are looking for research scientists with experience running a machine learning project from inception to completion, and specifically with a background and interest in NLP or Deep Learning.

We'll trust you to:

  • Drive projects as the principle point-of-contact, with the ability to determine and elaborate on suitable metrics as well as methods
  • Write, test, and maintain production-quality code (mainly C++)
  • Publish papers and attend conferences in leading venues representing Bloomberg

You'll need to have:

  • A graduate degree in a quantitative field (PhD preferred but not required)
  • Recent experience with C++ or Java
  • Strong computer science fundamentals (algorithms, data structures)
  • A track record of relevant research demonstrated by publications in NAACL, ACL, CVPR, ECCV, ICML, NIPS, ICLR, IJCAI, SIGIR, AAAI, KDD, or WWW
  • Solid background in machine learning and/or statistics, publication history
  • Experience with a deep learning framework (e.g., TensorFlow, PyTorch, Keras, CNTK, etc.) is helpful
  • Experience with NLP is also very useful
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