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Morgan Stanley

Manages investments and advises on financing

Assistant Vice President - Data Science & Analysis

Applied Machine LearningPosted on Nov 9
Full-timeJersey City, NJ, USA$150k /yr

About the Job

Requirements

  • A Master's degree in Data Science, Quantitative Economics, Mathematics, or a related field is required.
  • Two years of experience in the position offered, or two years as a Data Science & Analysis Associate, Machine Learning Researcher, or in a related role, are required.
  • Two years of experience developing end-to-end machine learning solutions, including data sourcing, feature engineering, evaluation, deployment, monitoring, and business outcome metrics, are required.
  • Two years of experience developing and benchmarking algorithms, including deep learning approaches for classification and regression, with experimentation to improve performance and robustness, are required.
  • Two years of experience designing and deploying agentic artificial intelligence solutions and applying generative artificial intelligence techniques to machine learning and deep learning models are required.
  • Two years of experience using Python for predictive modeling, data processing, feature engineering, statistical analysis, and workflow automation are required.
  • Two years of experience writing SQL queries for data extraction, transformation, aggregation, and analysis on enterprise-scale relational databases are required.
  • Two years of experience applying statistical analysis, hypothesis testing, and A/B testing methodologies to evaluate model and business performance are required.
  • Two years of experience applying feature engineering, unsupervised learning, text processing, and pattern discovery techniques to structured and unstructured datasets are required.
  • Two years of experience developing reports and visual analytics to communicate model performance, experimental results, and business insights to technical and non-technical stakeholders are required.
  • Two years of experience partnering with stakeholders to gather requirements, communicate analytical findings and model limitations, document decisions, and support governance processes for production analytics and machine learning solutions are required.
  • Experience validating machine learning models in collaboration with a validation team to ensure their accuracy and reliability is required.

Responsibilities

  • Develop data science solutions that can be tested and deployed to enable data-driven recommendations and outcomes.
  • Implement and scale high-availability models and algorithms for business and corporate functions.
  • Leverage machine learning modeling and algorithms for client acquisition use cases, including marketing, targeting, digital, and product strategy.
  • Build modeling solutions to solve business problems and lead the development of data science and modeling capabilities in the cloud transformation journey.
  • Investigate and create experimental prototypes for specific domains and verticals.
  • Analyze large, complex datasets to reveal underlying patterns, correlations, and trends quantitatively.
  • Support and enhance existing models to improve their performance.
  • Set up and conduct large-scale experiments to test hypotheses and drive business growth.
  • Collaborate with Legal, Compliance, Risk, Technology, and Business Partners to translate business needs into analytics solutions, align on model governance and controls, and ensure timely, compliant delivery.
  • Validate machine learning models in collaboration with the validation team to ensure accuracy and reliability.

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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