Morgan Stanley Machine Learning Summer Internship in New York, New York
The Quantitative Technology Machine Learning Research Summer Internship is an intensive 10-week program that provides Summer Associates the opportunity to work alongside Full-Time Finance professionals and ML specialists on impactful applied research projects. Summer Associates will work within Morgan Stanley’s Machine Learning Research Team for the entirety of the program. This is a highly motivated and collaborative team of scientists, technologists, and market practitioners. This team is responsible for working with business units and technology teams across the entire Firm to solve mission-critical high impact problems. The multi-faceted program features senior quant teach-in sessions, divisional speaker series, networking events, and community service. With individual coaching and continuous feedback, the program enables Summer Associates to experience and understand what a long-term career in ML Research within the Firm entails.
The Summer kicks off with a week-long introductory training program, which provides an institutional contextualization to the work that Summer Associates will be doing through market-knowledge training, finance workshops, coding and product training. Following the training week, Summer Associates will continue to receive more individualized on-the-job training as they begin their daily work and projects. Summer Associates will have a direct manager, as well as a program mentor, both of whom will act as invaluable resources throughout their time at Morgan Stanley.
Role and Responsibilities:
· Independently tackling previously-unsolved research problems that have commercial applications.
· Machine Learning and other advanced quantitative methods in every line of business; the purpose of the central ML Research team is to create custom algorithms and tailored solutions.
· Leverage the technical expertise and research acumen you have been cultivating in your academic careers, and apply it to real-world financial and operating problems. (Successful candidates will have experience in conducting creative, hands-on, high-impact quantitative research.)
· Broad experience across multiple fields is a plus.
· Track record of publishing in competitive venues is highly sought after.
Qualifications and Skills:
· You are pursuing a PhD degree in Computer Science, Mathematics, Physics, Statistics, Chemistry, Financial Engineering, Financial Math, Engineering, Quantitative Finance, or other related quantitative field.
· You have a deep understanding of statistical learning methods and strong mathematical academic training.
· You have excellent programming skills in Python or R, (C, C , Java, etc. is a plus).
· You have a keen interest in financial markets.
· You have the drive and desire to work in an intense team-oriented environment.
· You have strong communication and organizational skills.
Expected base pay rates for the role will be between 170000 and 185000 per year at the commencement of employment. However, base pay if hired will be determined on an individualized basis and is only part of the total compensation package, which, depending on the position, may also include commission earnings, incentive compensation, discretionary bonuses, other short and long-term incentive packages, and other Morgan Stanley sponsored benefit programs
Title: Machine Learning Summer Internship
Location: New York-New York
Requisition ID: 3241071