Data Scientist (Applied NLP)

New York, NY

Post Date: 06/27/2017 Job ID: 9890319 Industry: IT Perm
One of New York's fasting growing startups is experiencing its most rapid growth to date, the company needs a Data Scientist - Applied NLP. We're looking for someone who loves crunching through large amounts of text and synthesizing meaning out of it. You're excited to dive deep into the nuances of job description text that makes them different from all other classes of text. You enjoy working on a team but also get a thrill out of creating something from nothing, and you're looking forward to being part of the foundation of our data team.

Right off the bat, you'll be able to have an immediate impact on the team by writing extraction tools to grab important entities like compensation and work experience from our job descriptions. Specifically, you will:
  • Develop algorithms to extract key features from unstructured job text
  • Implement prototypes of the algorithms and models you design in Python, R, and/or scalable big data systems
  • Identify appropriate metrics to measure the success of our classification systems
  • Introduce, evaluate, and recommend machine learning technologies that may be relevant to our success (e.G., TensorFlow, Spark, etc.)
  • Generate algorithms and robust classification models to automatically tag, parse, and otherwise identify semi- and unstructured data
  • Develop recommendations for the product team for additional data we need to collect and how we might collect it in a scalable way
  • Potentially experiment with chatbot-based approaches to the job application process
Requirements:
  • Ph.D. Or Master's in Natural Language Processing, Machine Learning, or equivalent experience
  • An ability and eagerness to learn and teach others
  • Professional experience using applied NLP techniques to create fully-functioning prototypes or feature
  • Solid software engineering and scripting skills, preferably in Python
  • Working knowledge of relevant tools for NLP at scale, like Hadoop, Spark, etc.
  • Experience with common toolkits for deep learning, such as Theano, Tensorflow, Torch or Caffe preferred but not required
  • Experience with knowledge graphs or graph databases preferred

Jose Bustamante


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