Data Scientist SPG

New York, NY

Posted: 03/13/2019 Industry: IT Consulting Job Number: 11966658
The Securitized Products Technology Group (SPG) is responsible for all aspects of the company' s core applications that help traders manage positions and trades, calculate P&L, assess bond valuations, and calculate risk. This group is responsible a set of credit analysis tools that help identify trading opportunities, and we are building a team of NLP/Client professionals to build a platform of tools to enable trading/sales in revenue generation. 

The successful candidate will perform groundbreaking work in Natural Language Processing and Machine Learning methods, and will tailor them to front-office applications involving credit analysis, trading strategies, pricing models, and more. Projects may involve applying NER and sentiment analysis techniques to analyze corporate financial documents and news articles; or using state-of-the-art parsing methods to extract bond covenant information, and then using a training model to derive bond behavior under stressed scenarios. 

The ideal candidate for this would possess a combination of research and professional experience in the fields related to Natural Language Processing and Machine Learning. The person should be on the forefront of NLP/Client technologies, and be able to translate theory to projects that are deliverable on the commercial scale. 

Skills Required: 
• MS or PhD in Natural Language Processing, Machine Learning, or related field 
• 5+ years, a combination of professional and/or research experience 
• Apply different NLP techniques to areas such as sentiment analysis, classification, data/knowledge extraction, disambiguation 
• Expertise in NLP methods such as LSA, LDA, Semantic Hashing, Word2Vec, LSTM, BiDAF 
• Client experience with different supervised and unsupervised learning algorithms 
• Expertise in one or more programming languages: Java 8, Scala, Python, R, willing to consider others 
• Experience working with large, complex and diverse data sets from a variety of sources 
• StanfordCoreNLP/GATE experience a plus 
• Experience with Spark, or similar frameworks a plus 
• Publications on Client/NLP a big plus 

Ingrid Martinez

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