· Solve some of the most challenging problems in natural language processing, machine learning, and information retrieval including topical classification, legal sentiment analysis, user intent detection, open Q&A.
· Research, build, and deploy models based on both shallow and deep machine learning. Train robust NLP-based models a very large corpus of legal, regulatory, and news data.
· Apply machine learning techniques for improving search algorithms.
· Drive best practices for NLP/Machine Learning pipelines.
· Maintain current knowledge base of state-of-the-art ML algorithms (BERT, ELMo, GPT, etc.), API's, and open-source methods and be able to quickly evaluate alternatives.
· Translate complex business requirements into actionable stories with reasonable time estimates.
· Participate in model reviews with key stakeholders, including stakeholders with limited statistical backgrounds from among that set.
· Work with product leaders to apply data science solutions.
· Participate in knowledge sharing sessions (e.g. Guilds and Chapters).
DATA SCIENCE AND NLP SKILLS
· In-depth understanding of machine learning techniques such as classification, clustering, recommendation systems, and statistical models.
· 5+ years’ experience using Machine Learning and associated packages like scikit-learn, pandas, Numpy.
· Proficiency training large scale models in at least one modern deep learning engine such as Tensorflow, Keras, PyTorch/Torch, MXNet, Caffe/Caffe2
· 3+ years’ experience using NLP tools and methods such as OpenNLP, Stanford NLP, LDA, Gensim, spaCy
· 5+ years recent coding experience using Python AND/OR (Java OR Scala)
· SQL programming experience
· 2-3 years’ experience with a major cloud system (AWS, Azure, GCP)
· Familiarity with Cloud-based Machine Learning environments
TEAM AND SOCIAL SKILLS
· Strong collaboration and team skills