Natural Language Processing Engineer

Indianapolis based analytics consulting company is in search of a Natural Language Processing Engineer to be an in house subject matter expert for various nationwide data science projects.  Role may involve client facing responsibilities as well as mentorship to other data scientists on the team.

Job Description

The Natural Language Processing (NLP) engineer will join the growing analytics team and report to the Manager of Analytics. The team is responsible for inventing, developing, and deploying new models and techniques using healthcare data, large nationwide unstructured data sets, and Federal program data to improve administrative, clinical, and program effectiveness. The NLP engineer will contribute to the invention, development, and deployment of state-of-the-art NLP tools and analysis for various large complex clients.

Responsibilities

  • Designs and implements creative solutions for a broad range of NLP problems
  • Acts as a consultative resource to various clients and performs requirement gathering and needs assessments for various projects
  • Demonstrates deep knowledge of NLP and applications
  • Demonstrates proficiency in training and tuning NLP language models for best trade-offs for the application
  • Collaborates with machine learning, data science, and engineering teams for incorporating NLP capabilities into client solutions
  • Incorporates an expansive set of unit tests to provide reasonable test coverage and protection from regressions
  • Characterizes performance of solutions for adequate speed and scale
  • Documents solutions clearly and works with the QA team to ensure proper testing
  • Functions within an agile scrum team, embracing all tenets of scrum

Requirements

  • Bachelor’s Degree in Computer Science, Engineering, Information Systems or Math.
  • Masters’ Degree or advanced degree in Linguistics or Analytics.
  • Strong technical credentials, with at least 2 years of professional experience working in a relevant field: machine learning, deep learning, information retrieval, natural language understanding, etc.
  • Solid fundamentals in problem-solving, algorithm design, complexity analysis, mathematics, and statistics.
  • Proficiency in a major programming language (Python, Java, Scala or similar).
  • Hands-on experience with NLP/Machine Learning/Deep learning tools and libraries.