Morgan Stanley seeking for a Machine Learning Engineer who’s worked on large-scale data and machine learning systems before. The standard candidate will have the knowledge of machine learning (ML) algorithms and frameworks, as well as a background in data engineering. Engineering (programming), machine learning (ML), and data analysis are all part of the work. Knowledge of data science is advantageous. Morgan Stanley Wealth Management’s Decision Products, which is part of the Artificial Intelligence and Knowledge Management department, is hiring for this role. The crew is based in three cities: New York City, Mumbai, and Bengaluru, India. The team works with the firm’s many businesses and IT departments to develop analytics and machine learning-powered solutions that provide relevant recommendations to Clients, Participants, and Financial Advisors. The Digital Platforms team collects data from a variety of internal and external upstream sources to provide statistics, models, dashboards, and analytics.
The candidate must have the following responsibilities:
• Investigate new data sources and information. Choose relevant datasets and representation techniques.
• To extract inferences from data, perform data analysis (statistical and non-statistical).
• Create pipelines for ML model training, validation, and hyperparameter search.
• Data quality, validation, governance, and transparency are all ways to ensure data integrity.