Associate – Data & Analytics Engineering

Develop risk models including linear/logistic regressions, monte carlo simulations, present value calculations and other portfolio metric computations Collaborate with Quant strategists to model and develop mathematical risk calculations and predictions Curate large datasets, including account, demographic, transactional and market data for analysis, model training, and model inference Design and implement cloud computing frameworks to address the growing computational demands of larger models with increased parameters and data Maintain critical model infrastructure, including Symphony compute grids, distributed hash tables, and low latency caching tools Perform unit testing, component testing, integration testing to ensure high quality software is delivered Monitor applications and provide support in production Develop automated CI/CD processes for delivering quality software into production Work in an agile scrum team and contribute to agile processes

Morgan Stanley provides a variety of financial services, including investment banking, securities, wealth management, and investment management. The firm assists individuals, families, institutions, and governments in raising, managing, and distributing capital to meet their financial objectives. Its services are tailored to the specific needs of clients, utilizing a vast global network and expertise in the financial market. Morgan Stanley generates revenue through advisory fees, asset management fees, trading commissions, and interest income. What sets Morgan Stanley apart from its competitors is its strong commitment to core values such as client-first service, exceptional ideas, diversity and inclusion, and community engagement.