AI Research Scientist - NLP

New York City, NY, United States
Posted 15 days ago
Main Location
New York City, NY, United States
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News and social media move financial markets. Bloomberg is one of the largest producers of news in the world and ingests over 70,000 external news feeds and social media like Twitter each day. This data keeps our clients informed, and our team's insights help make sense of it for our customers.

Who are we? Bloomberg's Artificial Intelligence (AI) group: researchers and engineers who have a passion for solving complex problems. Our charter: to extract relevant, meaningful, tradable, and actionable information (pricings, earnings, recommendations and major events) from data (news, web, social media, and structured data) in real-time. Since our customers rely on this information to make swift financial decisions, we guarantee precision, accuracy and latency beyond most academic and industry standards.

We aren't just building products. The infrastructure and algorithms we develop are used across the company by data scientists. We publish papers, attend conferences and contribute back to the larger data science community whenever we can (

Who are you? A research scientist who wants to work in the areas of machine learning, natural language processing, information extraction, reinforcement learning, graphical models, recommender systems and knowledge graphs. You want to join a close-knit group and make a big impact.

We'll trust you to:
  • Work with researchers in our Engineering AI group on live systems
  • Publish research findings in leading academic venues and represent Bloomberg at industry conferences
  • Write, test and maintain production-quality code
  • Design, experiment and evaluate models
You'll need to have:
  • A PhD in AI, NLP, ML, Optimization, or equivalent experience in related fields
  • 5+ years of experience programming in C++, Python or Java
  • 3+ publications in top-tier conferences or journals (such as ACL, AAAI, SIGIR, KDD, EMNLP, ICML, NIPS or equivalent)
We'd love to see:
  • A quantitative background (Probability, Statistics, Linear Algebra, etc.)
  • Experience with distributed computational frameworks (YARN, Spark, Hadoop)
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