Institutional Equity, MSET Quantitative Research - Product

From global institutions to hedge funds, investors come to Morgan Stanley for sales, trading, and market‑making services across almost every type of financial instrument in the world’s financial markets. Morgan Stanley professionals use our network and technology to provide liquidity and sophisticated analysis, to manage risk and execute reliably in fast‑changing markets.

Morgan Stanley’s Institutional Equity Division (IED) is a world leader in the origination, distribution, and trading of equity, equity‑linked and equity‑derivative securities. Our broad and deep client relationships, market‑leading platform, and intellectual insights enable us to be a world‑class service provider to our clients for their financing, market access and portfolio management needs.

The Quantitative Research (QR) group designs, builds and maintains the models that drive the equity trading engines at Morgan Stanley. Our systems are used globally by both internal trading groups and clients of the firm. We utilize systematic, data‑driven approaches to understand how markets work and put those ideas in action. The team spans the disciplines of finance, econometrics, statistics, mathematics, machine learning and data analysis, with many team members well versed in multiple areas.

We are looking to hire highly talented, creative individuals who are enthusiastic about research and contributing to a leading‑edge team in an intellectually stimulating environment.

• Execution Consulting – applying knowledge of algorithmic trading engines to reduce execution slippage
• Perform bespoke, in‑depth client Transaction Cost Analysis (TCA) to enhance algo performance
• Equity market‑structure research & analysis – for example, deep dives into market impact, dark liquidity, smart order routing & algorithmic order placement

• 5‑7 years of experience in the financial sector with direct practical experience in equity markets
• Bachelor or Master’s Degree in Finance, Economics or Mathematics (including equivalents of CA, CFA, FRM, MMS, MBA). Engineering degree is preferred
• Able to demonstrate practical mastery of data analysis at scale
• Significant experience in any mathematical/high‑level programming language such as Python or R
• Exposure or knowledge of different equity and equity‑derivatives products is desirable
• Strong written and verbal communication skills
• Practical expertise in constructing data processing pipelines and enriched datasets from diverse sources – internal as well as external
• Strong analytical and reasoning skills; able to decompose complex problems and projects into manageable pieces; comfortable suggesting and presenting solutions

• Experience with Linux, shell scripts and automation via AI
• Understanding of KDB+ or other databases

If this role is deemed a Certified role, it may require the holder to meet mandatory regulatory qualifications or internal company benchmarks.

Interested in flexible working opportunities? Morgan Stanley empowers employees to have greater freedom of choice through flexible working arrangements. Speak to our recruitment team to find out more.

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. For more information, please visit