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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.

Training Program:

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.

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