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Morgan Stanley

Manages investments and advises on financing

Machine Learning & Workplace Analytics - WM Administration, Wealth Management

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeMumbai, Maharashtra, IndiaNo salary listedIn-person

About the Job

Requirements

  • A Master's or PhD degree in Computer Science, Engineering, Mathematics, Physics, or an equivalent quantitative field is preferred.
  • At least 5 years of professional experience in machine learning, with 10–14 years of overall experience; financial services experience is preferred.
  • Demonstrated breadth and depth in machine learning algorithms and applications, including classification, regression, recommender systems, clustering, and deep learning.
  • Ability to independently conduct applied machine learning research with commercial applications.
  • Proficiency in at least one modern programming language, such as Python or C++, or a related language.
  • Experience with code versioning systems such as GitHub or Bitbucket and experiment tracking systems such as MLflow.
  • Proficiency with computer science fundamentals, including object-oriented design, data structures, and algorithmic design.
  • Ability to work independently, solve problems creatively, and debug and maintain complex code.
  • At least 2 years in a client-facing position is preferred.
  • Ability to work collaboratively and transparently within a team and with cross-functional stakeholders.

Responsibilities

  • Design and develop end-to-end machine learning solutions that address Wealth Management business opportunities and produce measurable outcomes.
  • Develop and experiment with state-of-the-art algorithms.
  • Partner with model risk stakeholders to validate models and meet reliability and governance expectations.
  • Deploy machine learning models in production environments in collaboration with the MLOps team, and monitor model performance.
  • Plan and conduct A/B tests to quantify the incremental impact and effectiveness of machine learning solutions.
  • Build, grow, and establish partnerships with business stakeholders and Risk, Legal, and Compliance divisions.
  • Create presentations to communicate model performance, insights, and recommendations to stakeholders and the broader team.
  • Manage and coach associates.
  • Leverage large language models to build generative AI use cases supporting Wealth Management business verticals.
  • Monitor and recalibrate developed models and communicate their impact to key stakeholders.

Desired Qualifications

  • Experience with cloud or big data technologies such as Azure, AWS, Google Cloud, or Hadoop, or equivalent technologies.
  • Familiarity with deep learning frameworks such as PyTorch, TensorFlow, or PyTorch Geometric, or equivalent frameworks.
  • Experience with Graph Neural Networks, Reinforcement Learning, large language models, transformer-based models, or recommender systems.
  • Track record of publishing in peer-reviewed scientific journals.

About the Company

Morgan Stanley

Manages investments and advises on financing

Morgan Stanley advises companies and governments on financing and manages investments for institutions, individuals, and families. Its business combines investment banking and securities trading with wealth management and an asset-management division that invests across public and private markets. Bankers arrange stock and bond sales and advise on mergers, while advisors build client portfolios and fund managers invest money under agreed strategies. The firm earns advisory and management fees, trading revenue, commissions, and interest from lending and deposits. Morgan Stanley was founded as a partnership in 1935 and is headquartered in New York City.

Company size
10,001+
Company stage
IPO
Headquarters
New York City, New York
Founded
1935

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