Morgan Stanley is seeking Quantitative Modelers to join the new Market Modeling Group at Morgan Stanley.

Candidates must have demonstrated excellence in mathematics, programming, statistics and Quantitative modelers must have a background which would enable them to develop models that would positively impact the revenue-generating capabilities of their trader counterparts. This role will "add value" to the Firm through the creation of models and valuation tools to be used by trading desks across many asset classes.

Quantitative modelers will also conduct empirical research, and should be comfortable working with large data sets in support of investment, trading and risk management decisions.

Responsibilities:

• Creating models and strategies that the desk will use to drive trading decisions.

• Creating pricing and marking models and tools for securities that are currently on the books or about to be purchased or bid on.

• Creating trader efficiency tools.

Requirements include:

• Strong Programming skills (C/C++) and ability to integrate models into existing analytical libraries and trading systems.

• Strong mastery of specific areas of math used in finance which include stochastic calculus, probability theory, statistics, partial differential equations and numerical analysis.

• PhD in pure or applied mathematics, physics, statistics, engineering or computer science.

Please note: Candidates must be authorized to work in the U.S. Principals only!

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Morgan Stanley is an equal opportunity employer and does not discriminate on the basis of race, color, religion, gender identity, sexual orientation, national origin, age, citizenship, disability, marital status, pregnancy, veteran status or any other characteristic protected by law. Morgan Stanley complies with applicable federal, state and local laws prohibiting discrimination in employment in every jurisdiction in which it maintains facilities. Morgan Stanley also provides reasonable accommodation to individuals with disabilities in accordance with its obligations under applicable law.

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