Temporary Quantitative Modeling Jobs (NOW HIRING)

We are looking for a Quantitative Desk Strategist who combines strong quantitative modeling skills, fixed income derivatives knowledge, and hands‑on software development experience.

This role sits within the Strats organization and works closely with the trading desk. The focus is on developing analytics for complex fixed‑income products and building real‑time risk systems that support daily trading decisions. It is a hands‑on role that requires close collaboration with traders and strategists to solve practical trading problems.

The ideal candidate can understand market risk, derivative pricing, and trading workflows, then translate those needs into practical models, scalable system design, and production‑quality code. This role requires someone comfortable working across models, data, infrastructure, and user workflows, while keeping the desk’s real‑time needs front and center.

The ideal candidate can communicate clearly with both technical and non‑technical audiences.

You will questions such as:

• How should we model, price, and risk‑manage products such as Total Return Swaps, Tender Option Bond Trusts, bond options, interest rate swaps, and rates forwards?
• How can we measure and explain risk across positions, products, curves, scenarios, as market moves in real time?
• How do we build systems that are reliable, fast, and intuitive enough for traders to use during the trading day?
• How can complex derivative analytics be turned into tools that improve trading decisions?
• How do we design systems that are scalable, maintainable, and resilient under market pressure?

• Develop quantitative models and analytics for pricing, risk, inventory, market impact, and trading performance.
• Build reliable tools and workflows used directly by traders and strategists.
• Analyze large, noisy, real‑time datasets to identify patterns, risks, and opportunities.
• Explain model results, assumptions, limitations, and trade‑offs to both technical and non‑technical audiences.Partner closely with traders to improve decision‑making across bonds, futures, ETFs, derivatives, and related products.
• Investigate P&L drivers and distinguish repeatable edge from temporary market conditions.
• Contribute to scalable systems that connect trading decisions across instruments, products, and regions.

• Master’s or Ph.D. in Mathematics, Physics, Engineering, Operations Research, Computer Science, Statistics, or similar quantitative fields.
• Strong coding skills; willingness to learn Scala quickly is required. Prior Scala or Python experience is a strong plus.
• Solid foundation in probability, statistics, numerical methods, and data modeling.
• Ability to communicate complex ideas clearly using data, mathematics, and practical examples.
• Curiosity about markets and willingness to learn bonds, ETFs, futures, and derivatives quickly.
• Comfort having your ideas challenged and challenging others constructively.
• Strong ownership, practical judgment, and attention to detail.
• A genuinely good sense of humor.

• AI‑assisted coding experience.
• Experience with kdb/q or other high‑performance time‑series databases.
• Experience with Java, C++, or distributed systems.
• Familiarity with machine learning techniques such as logistic regression, random forests, clustering, or classification models.
• Prior exposure to fixed income, electronic trading, market microstructure, or risk management.
• Experience building large‑scale, transaction‑processing, or real‑time decision systems.

Expected base pay rates for the role will be between $150,000 - $200,000 per year for Associate 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.

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.