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Morgan Stanley Investment Research is one of the financial industry's dominant thought leaders in equity and fixed-income investing and is a vital link between the Firm's varied business divisions. Our analysts, economists, and strategists have earned this reputation through timely, in-depth analysis of companies, industries, markets, and the world's economies. Our highly regarded equity analysts--who cover over 2,300 stocks globally and are organized by country, region, and global industry--develop key investment ideas and themes that are used by buy-side firms to structure portfolios as well as by the Morgan Stanley sales force in its interaction with investing clients; and provide valuable insights on market-moving events to the firm's traders and their clients. A career in investment research at Morgan Stanley demands a commitment to excellence and a passion for the markets as well as the highest level of integrity.
Data Management Organization (DMO) is leading the charge on data strategy and management in MS Research. Given the growing strategic importance of data, the Research DMO is a key enabler to both the "Offence" (generating new commercial opportunities) and "Defense" (ensuring proper data use and risk management). The group is seeking a self-starter Sector Quant with previous experience in data analysis and modeling. The role is dynamic, fast paced and interacts with multiple stakeholders.
The Sector Quant will work closely with the Equity Analyst teams and other SMEs to design models, extract insights and make recommendations on existing data products and new ones.
Responsibilities would include:
Combine quantitative processes with fundamental insights to identify industry key performance indicator, develop sector-specific signals, build conviction on a call, predict stock returns, and track company specific risks etc.
Build tools to query, clean, analyze raw data through databases, and design, fit, implement, debug statistics models to test the efficacy of sector data
Explore and evaluate alternative data to gain insights into new alpha
Publish leading research insight notes and present at industry conferences
Partner closely with sales/marketing, providing quant proof statements to both internal and external clients
Work closely with data and technology team to ensure data quality and delivery
Actively source new ideas and collaborate with other research teams
Advanced degree in quantitative field such as statistics, computer science, engineering, mathematics or finance, PhD preferred
1-5 years' experience in data analysis and modeling, proficiency working with large dataset, statistical/econometric methods, machine learning, data mining, and numerical methods
Strong programming skills including Q/KDB, C/C++, R, Python, Matlab, JAVA
Creative thinking and problem-solving skills; able to decompose complex problems into manageable pieces
Strong verbal and written communication skills; able to present quant solutions clearly to both internal and external clients
Team oriented; able to collaborate with a range of functional teams and resolve conflicts as necessary
Knowledge/experience in equity factor model and fundamental research a plus