Morgan Stanley's Wealth Management division is looking to solve business opportunities using machine learning solutions, delivering tangible business outcomes to 20M+ clients.
Requirements
- Demonstrated breadth and depth in knowledge and applications of machine learning algorithms in classification, regression, recommender systems, clustering, deep learning
- Proficiency in autonomously conducting applied ML research with commercial applications.
- Proficiency in at least one of the modern programming languages (Python, C++, or a related language).
- Experience with code versioning systems such as Github, Bitbucket, and experiment tracking systems like MLFLow.
- Proficiency with computer science fundamentals in object-oriented design, data structures, and algorithmic design.
- Experience with Cloud or Big Data technologies such as Azure, AWS, Google Cloud, Hadoop, or an equivalent
- Familiarity with Deep Learning frameworks (PyTorch, Tensorflow, PyTorch – Geometric, or equivalent).
Responsibilities
- Design and develop end-2-end machine learning solutions to address business opportunities in Wealth Management, delivering tangible business outcomes.
- Strive to develop and experiment with State-of-the-Art algorithms.
- Validate the machine learning models in collaboration with the validation team to ensure the accuracy and reliability of ML models.
- Deploy the machine learning models in production environments, in collaboration with the MLOps team, and monitor their performance.
- Conduct A/B tests to demonstrate efficacy of ML solutions.
- Participate in code reviews from both sides of the process.
- Build, grow, and establish partnerships with business stakeholders, marketing as well as with our Risk, Legal, and Compliance divisions.
Other
- Master’s or a PhD degree (preferred) in Computer Science, Engineering, Mathematics, Physics, or an equivalent quantitative field.
- At least 3 years of professional experience in Machine Learning.
- Experience communicating with business stakeholders.
- Proficiency in English.
- Track record of publishing in peer-reviewed scientific journals.
