We are a small, team of researchers and developers. We build algorithms for trading stocks, bonds, and derivatives at Morgan Stanley. Our work sits at the intersection of stochastic control, statistics, financial derivatives and numerical methods.
We are looking for a Statistician or Control Theorist who wants to work on market problems where the mathematics really matters.
The problems we study include:
Hedging multi-billion-dollar transactions using derivatives and dynamic risk-transfer strategies.
Optimizing large bond inventories to serve thousands of clients while managing risk, liquidity, and capital.
Using stochastic optimal control to combine instruments with different temporal dynamics into unified market making portfolio
Building models to price hundreds of thousands of instruments from sparse and noisy market observations.
Developing derivative pricing and hedging models that are robust enough for real trading environments.
This is not a role where mathematics is decorative. We expect you to formulate models, challenge assumptions, do challenging statistical analysis of data, write simulations, to turn insights into profitable trading policies and risk management tools.
The ideal candidate is comfortable moving between theory, computation, and empirical evidence. You might come from applied mathematics, statistics, operations research, probability, theoretical physics, stochastic control, or a related field. You do not need to know every corner of finance, but you should be excited by markets as a source of difficult and beautiful mathematical problems.
To understand the flavor of the work, consider papers such as:
“High-Frequency Covariance Estimates with Noisy and Asynchronous Financial Data” — Aït-Sahalia, Fan & Xiu
“Algorithmic Market Making in Dealer Markets with Hedging and Market Impact” — Barzykin, Bergault & Guéant
If one of these papers makes sense to you, we would like to hear from you.
If both make sense to you, please apply immediately.
Requirements
Ph.D. in Applied Mathematics, Statistics, Operations Research, Theoretical Physics
Strong mathematical maturity and ability to reason from first principles.
Advanced Data Analysis skills
Ability to program well enough to turn ideas into working models or prototypes.
Clear communication skills: you should be able to explain complex ideas to both technical and non-technical colleagues.
Working knowledge of probability, statistics, stochastic calculus, optimization, or stochastic control.
Desire to work independently
A good sense of humor.
Nice to Have
Knowledge of derivatives mathematics such as option pricing and credit default swaps.
Experience with noisy data, sparse estimation, dimensionality reduction and numerical optimization
Expected base pay rates for the role will be between$150,000 - $200,000per year for Associate and between $225,000 - $250,000 for Vice President at the commencement of employment. However, base pay if hired will be determined on an individualized basis and is only part of the total compensation package, which, depending on the position, may also include commission earnings, incentive compensation, discretionary bonuses, other short and long-term incentive packages, and other Morgan Stanley sponsored benefit programs.
