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.
Technology Information Risk (TIR)
TIR's mandate is to enable the Firm to manage its technology and data related risks through implementing proactive, comprehensive, and consistent risk management practices across the Firm to protect the franchise while capturing business opportunities. The TIR team partners with the business by ensuring that Technology understands how to manage, escalate and monitor risk.
The right candidate will assist in developing the functional testing of limit controls and other key E-Trading controls. This is an important deliverable to meet regulatory an internal audit requirements for second line of defense of our trading systems. This will be an ongoing role with increase in features of the system as more E-Trading flow is covered by this system as it goes global. Ideal candidate will have experience in Machine Learning and in applying Machine learning techniques for solving business problems like Fraud / Anomaly detection. Experience in trading systems would be a big plus.
Minimum of three years of experience in the following areas: Spark ML, Statistical Concepts, Programming in Python/R, Java/Scala, Relational databases
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