Applied Machine Learning Scientist/Engineer - Relevance & Discoverability team

Careers at Bloomberg

New York

Posted Oct 7, 2016 - Requisition No. 54893

Information and data move the financial markets. Bloomberg ingests more than 70,000 different news feeds, tracks million of securities, analyzes proprietary data sources such as supply chain information for the entire world, and keeps track of many large sources of data to help our clients stay in the know. This data would be unmanageable without our help.

Who are we? Bloomberg's Information Retrieval Group - a group of specialists, researchers and software engineers who have a passion for solving complex problems. We are building machine learning models to analyze the connectedness between entities within the financial ecosystem.

Who are you? A research scientist and engineer who wants to apply machine learning to solve challenging problems. You want to be part of a small team making a big impact and are not afraid to get your hands dirty in data.

We'll trust you to:

  • Design and build machine learning systems that solve difficult problems involving knowledge graphs and big data
  • Write, test and maintain production-quality Java, C++, and/or Python code
  • Study and analyze problems, propose solutions and design experiments

You'll need to have:

  • A PhD or Master’s in Machine Learning, Natural Language Processing or equivalent experience
  • 3+ years of experience programming in C++, Python or Java
  • 3+ publications in top-tier conferences or journals in NLP or ML (such as ACL, EMNLP, ICML, NIPS, CIKM, WWW, or KDD)

We'd love to see:

  • A mathematical background (Probability and Statistics)
  • A working knowledge of DNNs
  • A working knowledge of Spark
  • Experience with Knowledge Graphs

If this sounds like you, apply! If you are a good fit, we'll invite you to our New York office to present your work.

You can also check out our Bloomberg Labs Website ( to learn how our data scientists apply methods from machine learning, natural language processing and search to complex problems across the company.

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