Quantitative Research

From global institutions to hedge funds, investors come to Morgan Stanley for sales, trading, and market-making services in almost every type of financial instrument in all 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 the 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 which 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 enthusiastic about making a contribution to a leading-edge team, in an intellectually stimulating environment.
 

Primary Responsibilities

The key elements of the role are –

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

  Core Requirements

We are looking for a confident and outgoing person, who has exceptional attention to detail and takes initiative.

• 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/R
• Exposure/knowledge of different equity and equity derivatives products is desirable
• Strong written and verbal communication skills