Institutional Equity, MSET Quantitative Research - Product
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 ResponsibilitiesThe key elements of the role are –Execution Consulting. Applying knowledge of algorithmic trading engines to reduce execution slippagePerform bespoke, in-depth client Transaction Cost Analysis (TCA) for enhancing algo performanceEquity Market structure research & analysis – for example, deep dives into market impact, dark liquidity, smart order routing & algorithmic order placement. Core RequirementsWe 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 marketsBachelor or Master's Degree in Finance, Economics or Mathematics (Including equivalents of CA, CFA, FRM, MMS, MBA). Engineering degree is preferredAble to demonstrate practical mastery of data analysis at scaleSignificant experience in any mathematical/high-level programming language such as Python/RExposure/knowledge of different equity and equity derivatives products is desirableStrong written and verbal communication skillsPractical expertise in constructing data processing pipelines and constructing enriched datasets from diverse sources - internal as well as externalStrong analytical and reasoning skills; able to decompose complex problems and projects into manageable pieces; comfortable suggesting and presenting solutionsComplementary SkillsExperience with Linux, shell scripts and automation via AIUnderstanding of KDB+ or ...