ED/VP - Quant Researcher ED/VP - Quant Researcher …

Morgan Stanley
in Hong Kong
Permanent, Full time
Last application, 29 Jul 21
Competitive
Morgan Stanley
in Hong Kong
Permanent, Full time
Last application, 29 Jul 21
Competitive
ED/VP - Quant Researcher

Group:

The Quantitative Research (QR) group designs, builds and maintains the models which drive the equity trading engines at Morgan Stanley. Our systems are used globally by both internal trading groups and clients of the firm. We utilize systematic, data-driven approaches to understand how markets work and put those ideas in action. The team spans the disciplines of finance, econometrics, statistics, mathematics, machine learning and data analysis, with many team members well versed in multiple areas. We are looking to hire highly talented, creative individuals who are enthusiastic about research; and enthusiastic about making a contribution to a leading-edge team, in an intellectually stimulating environment.

Opportunity:

We are looking for a VP/ED level quantitative researcher for our quantitative research team, in Hong Kong. Quantitative researchers collaborate closely with quantitative researchers, MSET business partners and Technology to enhance the performance and product offering of our equity trading algorithms.

The role will cover but not be limited to model selection and calibration for the many quantitative sub-problems our algorithms need to solve. Our current research spans a wide area, covering covariance matrix estimation, factor modeling, NLP, and the use of machine learning in modeling market microstructure. We are particularly interested in interpretable ML.

The candidate will also be involved in client communication: guiding clients to the algorithm that best suits their trading style, explaining the behaviour of our algorithms, designing statistical frameworks to help clients measure their trading performance generally.

Core Requirements:
  • A PhD/Masters from a strong program that focuses on Machine Learning/Data Science/Computer Science/Physics/Mathematics/Statistics is preferred.
  • Able to demonstrate practical mastery of key ML techniques
  • Significant experience in any mathematical/high-level programming language
  • Strong written and verbal communication skills.
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