We are solving today’s most complex analytics problems, making the lives of our colleagues easier and more productive, and driving our mission to deliver exceptional solutions to our customers. We are passionate about learning new ways to get the most value from our massive data resources. We are partnering to incorporate analytics into every aspect of the enterprise. Developing ourselves and others is key to our success.

RESPONSIBILITIES

As a Sr. Data Scientist authority in these areas you will be responsible for researching, developing, and improving algorithms that help computers learn from text. Our goal is to reduce the time and expense of performing traditionally manual tasks, growing efficiency and reducing costs. By extracting data sets containing millions of documents, you will help to develop NLP capabilities to improve the speed and ease with which we service our client.  Additionally, you will be able to responsible for:

• Conducting state of the art research in Natural Language Processing (NLP and NER)
• Research and application of state-of-the-art deep learning techniques to inform key strategic recommendations and decisions
• Advising/mentoring data scientists and business partners on applying NLP in their work
• Training staff and clients on AI/ML and ML/DL techniques

QUALIFICATIONS

• Expertise developing natural language processing/understanding algorithms/models required
• Expertise applying deep learning techniques to NLP/U problems required including thorough knowledge of the theory and practice of NLP and deep-learning techniques
• Strong experience in other machine learning, or artificial intelligence algorithms/models required
• Strong coder, with experience building models and analyzing data using machine learning tools (Python, Matlab) and deep learning tools (TensorFlow, Keras). Software development experience a plus.
• Strong experience implementing models in production
• Ability to craft new concepts and stay current with academic research. Published research a plus.
• Strong experience working with non-technical stakeholders.
• Ability to summarize research and analysis for audiences with varying levels of expertise.