Technical Lead, Natural Language Processing Research Engineer

Company Profile
Morgan Stanley is a leading global financial services firm providing a wide range of investment banking, securities, investment management and wealth management services. The Firm's employees serve clients worldwide including corporations, governments and individuals from more than 1,200 offices in 43 countries.
As a market leader, the talent and passion of our people is critical to our success. Together, we share a common set of values rooted in integrity, excellence and strong team ethic. Morgan Stanley can provide a superior foundation for building a professional career - a place for people to learn, to achieve and grow. A philosophy that balances personal lifestyles, perspectives and needs is an important part of our culture.

Technology works as a strategic partner with Morgan Stanley business units and the world's leading technology companies to redefine how we do business in ever more global, complex, and dynamic financial markets. Morgan Stanley's sizeable investment in technology results in quantitative trading systems, cutting-edge modelling and simulation software, comprehensive risk and security systems, and robust client-relationship capabilities, plus the worldwide infrastructure that forms the backbone of these systems and tools. Our insights, our applications and infrastructure give a competitive edge to clients' businesses-and to our own.

MS Wealth Management (MSWM) Technology
Morgan Stanley Wealth Management (MSWM) Technology is the global technology department responsible for the design, development, delivery and support of the technical solutions behind the products and services used by the Morgan Stanley Wealth Management (MSWM) business. The department is comprised of 10 organizations: Sales, Banking & Corporate-Client Technology, Investment Products & Markets Technology, Client Reporting, Core Processing, Private and International Wealth Management Technology, Technology Integration Office, Enterprise Infrastructure & Production Management, Capital Markets Application & Data Services, Deployment Planning & Release Management, and the Chief Operating Office. Morgan Stanley Wealth Management (MSWM) Technology works with large scale databases such as DB2 and SQL Server, proprietary and non-proprietary messaging software, a broad variety of vendor products, numerous financial exchanges and regulatory entities, and programming languages ranging from .Net and Java to Cobol and VB.Net.

Position Description
Candidate will work in the newly formed Artificial Intelligence team in Morgan Stanley Wealth Management. Candidate will be doing hands-on Research and Development and will be responsible for delivering NLP-based products in the financial domain. Products may span Deep/Shallow Question Answering, Search, ChatBots to enable various operation tasks, client assistance based on inferred client needs, Virtual Assistant to Financial Advisors etc. It is expected that the team will grow as business needs grow and candidate should be able to mentor and guide other NLP Research Engineers to build, release and maintain these products.


Primary Skills / Must have
- Experienced professional with minimum 8 years of experience doing research and development, building NLP-based systems in one or more areas below:
- QA Systems: Experience developing end-to-end Statistical and/or Deep Learning NLP systems or components for Topic detection and modeling, Question Answering, text/document retrieval, text classification, sentiment analysis etc.
- Dialogue System: Experience developing end-to-end systems or components for conversational dialogue systems.
- Must be a self-starter and have excellent communication and presentation skills.
- Must have experience leading small teams formally or informally.
- Experience working as a part of a distributed team.
- Must be able to liaise with business execs, understand business requirements and turn them into technical requirements as we diversify.
- MS or Ph.D. in Computer Science, Computational Linguistics, Electrical Engineering or related disciplines.

Secondary Skills / Desired skills
- Experience working with DBs, Knowledge graphs, Ontologies.
- Experience with UIMA based development, NL toolkits such as NLTK, Scikit-learn, Stanford NLP, Keras, Tensor Flow, Theano and other DL toolkits.
- Experience developing and releasing a commercial/scalable NLP-based product.
- NLP experience in the Financial Domain.
- Experience creating and evaluating systems with WikiQA, SQuAD *LI-AG1

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