Machine Learning, Assistant Vice President

Morgan Stanley

Confirmed live today High trust

Quick summary

Work type: On-site
Location: NY, NY
Salary: $85,000–$140,000 / yr
Employment: Full-time
Posted: 11 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $216k

This role $112k

$62k $298k

below market most similar roles pay here above market

This role pays less than 99% of similar roles. Most pay $177,737–$254,750 — the blue band above. At the midpoint, this role pays about $112k versus about $216k for comparable roles.

Based on 240 similar postings.

Employer

About Morgan Stanley

Morgan Stanley is a global financial services firm providing investment banking, securities, wealth management, and investment management services to corporations, governments, institutions, and individuals. Industry: Investment Banking & Financial Services

Morgan Stanley currently has 40 open roles on FindRole.

Listed pay typically runs $154,000–$214,000 across 34 roles with salary data.

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At a glance

TL;DR · Machine Learning, Assistant Vice President

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The Machine Learning, Assistant Vice President joins the Wealth Management Strategy & Analytics division to develop end-to-end machine learning solutions. This role involves ideating, prototyping, and shipping models to address business opportunities across various client channels and product organizations. Key responsibilities include designing state-of-the-art algorithms, validating model accuracy with specialized teams, deploying solutions into production environments, and conducting A/B tests. The candidate must utilize Python, C++, and deep learning frameworks like PyTorch or TensorFlow to build recommender systems, graphical neural networks, and large language models. Technical requirements include proficiency in object-oriented design, data structures, and experiment tracking systems like MLFlow. The work focuses on applying research in classification, regression, and clustering to solve complex wealth management problems and deliver personalized client experiences.

Skills

Machine Learning Python C++ PyTorch TensorFlow LLMs Graphical Neural Networks MLOps AWS Azure Cloud Hadoop MLflow GitHub Bitbucket Deep Learning Recommender Systems Reinforcement Learning

What you'll do

Design and develop end-to-end machine learning solutions to address Wealth Management business opportunities.
Experiment with and develop state-of-the-art algorithms for various machine learning applications.
Validate machine learning models with the validation team to ensure accuracy and reliability.
Deploy machine learning models into production environments and monitor their ongoing performance.
Conduct A/B tests to demonstrate the efficacy of implemented machine learning solutions.
Participate in peer code reviews throughout the development process.
Create presentations to showcase modeling results to internal stakeholders and team members.

What we're looking for

Master’s or a PhD degree in Computer Science, Engineering, Mathematics, Physics, or an equivalent quantitative field (preferred).
At least 3 years of professional experience in Machine Learning.
Demonstrated breadth and depth in machine learning algorithms including classification, regression, recommender systems, clustering, and deep learning.
Proficiency in autonomously conducting applied ML research with commercial applications.
Proficiency in at least one modern programming language such as Python or C++.
Experience with code versioning systems like Github or Bitbucket and experiment tracking systems like MLFlow.
Proficiency in computer science fundamentals including object-oriented design, data structures, and algorithmic design.
Experience communicating with business stakeholders and proficiency in English.

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