Applied Scientist - Question Answering
New York, NY
Posted Mar 8, 2019 - Requisition No. 74017
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.
Who are we? Bloomberg's Machine Learning Group - a group of scientists, researchers and software engineers who have a passion for solving complex data problems.
Our Question Answering Team
We build systems that enable our clients to ask the Terminal complex questions in natural language. We tackle a range of challenging problems in NLP that require sharp research instincts and solid engineering skills. We are looking for research scientists and software engineers with NLP experience, and specifically with a background and interest in one or more of the following areas:
- General statistical NLP (sequence labeling algorithms, language models, etc.)
- Syntactic and semantic parsing (e.g., top-down, bottom-up, charts, dependency parsing, PCFGs, semantic-driven parsing based on CCGs and the lambda calculus, etc.)
- Formal computational semantics
- Deep learning and distributional semantics, preferably with practical experience using at least one DL framework like TensorFlow or PyTorch
- Ontologies and knowledge engineering, particularly as used in knowledge graphs for question answering
We are excited to meet researchers/engineers who want to be part of a team making a big impact and are not afraid to get their hands dirty in data.
We'll trust you to:
- Design and build systems that solve difficult problems in NLP and particularly in QA
- Write, test and maintain production-quality C++ and Python code
- Publish in leading academic venues and represent Bloomberg at industry conferences
You'll need to have:
- PhD (or Masters with 3+ years of industry experience)
- Solid background in natural language processing and/or machine learning (as outlined above)
- Strong Computer Science fundamentals (algorithms, data structures)
- Familiarity with C++ is strongly preferred, and functional language programming (ML, Haskell, Scala, etc.) is a big plus.