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About the Role
Join a quantitative team supporting a large municipal bond market-making desk, utilizing mathematics, statistics, machine learning, and software to solve practical trading problems. The role involves analyzing trading strategies, building algorithms, modeling financial risks, and analyzing trading profits and losses. You will work directly with traders, quantitative researchers, and engineers to identify trading strategies, assist with complex trades and hedging, and improve pricing and risk models.
Responsibilities
- Research and test quantitative trading strategies.
- Help traders evaluate complex transactions, hedge selection, position sizing, and execution timing.
- Develop pricing and risk models for municipal bonds, bond derivatives, and related products.
- Analyze inventory risk, trading activity, and profit-and-loss performance.
- Apply statistics and machine learning to trading, pricing, and risk-management problems.
- Help move machine-learning and AI models into production.
- Organize and maintain quantitative models, research code, and development environments.
- Communicate analytical findings clearly to traders and other stakeholders.
Requirements
- Bachelor’s degree in mathematics.
- Masters degree in STEM, preferably Applied Math, MFE, Operations Research, Statistics, Physics, Engineering.
- Strong knowledge of probability, statistics, numerical methods, and mathematical modeling.
- Good programming skills, preferably in Python.
- Familiarity with, or an interest in learning, Linux, Git, package management, containers, pandas, and NumPy.
- Strong interest in trading and financial markets.
- The ability to take ownership of software, models, and research processes.
- Excellent analytical, organizational, and communication skills.
- A collaborative personality and an interest in working closely with PEOPLE on trading desk.
- Ability to stay calm under pressure.
- Positive, can do, extrovert personality.
- Experience with fixed income, derivatives, bond mathematics, JavaScript, kdb+/q, machine learning, or production model deployment is helpful but not required.
- Recent graduates and candidates with up to three years of relevant experience are encouraged to apply.
- Prior municipal bond experience is not required.
Skills
- Python
- Linux
- Git
- Package management
- Containers
- Pandas
- NumPy
- Fixed income
- Derivatives
- Bond mathematics
- JavaScript
- kdb+/q
- Machine learning
- Production model deployment
Location
- 42 countries
Work Type
- Full-time
Experience Level
- Up to three years of relevant experience
- Recent graduates
Education Level
- Bachelor’s degree in mathematics
- Masters degree in STEM, preferably Applied Math, MFE, Operations Research, Statistics, Physics, Engineering
Salary/Compensations
- $110,000 - $125,000 per year (Analyst)
- $150,000 - $200,000 per year (Associate)
Benefits
- Commission earnings
- Incentive compensation
- Discretionary bonuses
- Other short and long-term incentive packages
- Morgan Stanley sponsored benefit programs
About the Company
- At Morgan Stanley, we raise, manage and allocate capital for our clients – helping them reach their goals.
- We have been in business for 90 years.
- Our values include putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back.
- We have over 80,000 employees in 1,200 offices across 42 countries.
- We offer an environment where employees are supported and empowered.
- Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences.
- We support employees and their families with comprehensive employee benefits and perks.
- There is ample opportunity to move about the business for those who show passion and grit in their work.
- To learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-offices into your browser.
Equal Opportunity
- Morgan Stanley is an equal opportunity employer committed to building and maintaining a workforce that is diverse in experience and background.
- Our recruiting efforts reflect our strong commitment to a culture of inclusion, where individuals are hired, developed, and advanced based on their skills and talents.
- Our workforce reflects a broad cross-section of the global communities in which we operate, bringing a variety of backgrounds, talents, perspectives, and experiences.
- For more information, please visit: https://www.morganstanley.com/people-opportunities/eeo.