The Bloomberg Verticals group provides best-in-class tools, search and analytics for several Bloomberg products in the areas of Law, Government and New Energy Finance. Our Machine Learning team is looking for an experienced data scientist to join and contribute to building innovative legal research products using Natural Language Processing (NLP) and Machine Learning. Our group extracts knowledge from hundreds of millions of legal documents and builds intelligent models to enable our customers to get the right answers quickly.

The team works closely with product managers, software engineers, content data team members and market strategists. We apply NLP and Machine Learning techniques to text such as entity extraction and disambiguation, text classification and clustering.

You'll need to have:

• A B.S, M.S. or PhD. in Computer Science, Computer Engineering, Applied Mathematics or a related field
• 3+ years of experience with Machine Learning, Statistical Models, NLP and Text Analytics on large data sets
• Experience with techniques such as topic modeling, text classification, entity extraction and disambiguation
• A solid understanding of machine learning techniques including Support Vector Machines (SVM), Logistic Regression, Decision Trees, Max entropy, Conditional Random Fields (CRF) and Unsupervised Learning Methods
• 1+ year of experience programming in Python
• Experience using R, or other data science toolkits, such as Scikit-learn, NLTK, WEKA, Mallet, CLUTO and GENSIM

We'd love to see:

• Experience in all phases of machine learning application lifecycles from data gathering and preparation to optimizing model performance
• Publications or presentations in relevant communities (ICML, NIPS, CVPR, SIGIR, ACM Multimedia)
• Legal or financial domain experience