Data Scientist (NLP and GenAI Specialist)

Morgan Stanley; Dallas (TX); On-site; USD 160,000 - 230,000; Full time

Job summary

Morgan Stanley seeks a Data Scientist (NLP Specialist) in Non-Financial Risk to develop and deploy AI models for surveillance and compliance monitoring. The role focuses on NLP, ML, and quantitative methods within the Legal & Compliance division, partnering across Compliance, Legal, and IT to advance detection of financial crimes.

Ideal candidates have 5+ years in AI/ML/NLP with Python, experience with LangChain, PyTorch, and OpenAI SDK, and a strong analytics mindset.

Qualifications

• Master's or PhD in highly quantitative field.
• 5+ years of hands-on AI/ML/NLP experience for business problems.
• Strong Python or Java and software design knowledge.
• Experience with LangChain, PyTorch, HuggingFace and related tools.
• Familiarity with SDLC and Git operations.

Responsibilities

• Design high-performance systems using LLMs, RAG, and graph analytics.
• Create GenAI solutions to automate tasks and reduce costs.
• Research novel methods to enhance analytical solutions.
• Collaborate with Compliance, Legal, Financial Crimes, and IT.
• Champion innovative approaches to detect suspicious activity.

Skills

NLP

ML

Python

Communication

Problem solving

Education

Master's degree in CS/ML

PhD in a quantitative field

Tools

LangChain

LangGraph

Semantic Kernel

OpenAI SDK

PyTorch

HuggingFace

Git

Job description

We're seeking someone to join our team as a Data Scientist (NLP Specialist) in Non-Financial Risk to develop and deploy advanced AI models using NLP, Machine Learning, and quantitative techniques to improve surveillance and compliance monitoring.

In the Legal & Compliance division, we assist the Firm in achieving its business objectives by facilitating and overseeing the Firm's management of legal, regulatory, and franchise risk. This is a director level position within the NFR Data & Analytics team, which is responsible for designing and optimizing surveillance models and tools using advanced analytical techniques to help identify suspicious and/or illegal behaviors like money laundering, market manipulation, insider trading, unfair sales or trading practices and other financial crimes.

Since 1935, Morgan Stanley is known as a global leader in financial services, always evolving and innovating to better serve our clients and our communities in more than 40 countries around the world.

What you'll do in the role:

• Design high-performance systems leveraging cutting-edge techniques including Large Language Models (LLMs), Retrieval Augmented Generation (RAG), Agentic AI architecture, and knowledge graph analytics.
• Create GenAI-based solutions to automate manual tasks and drive cost efficiency.
• Conduct research to identify novel methods for enhancing analytical solutions.
• Collaborate with stakeholders across Compliance, Legal, Financial Crimes, and IT to promote adoption of new AI/ML/NLP capabilities.
• Champion innovative approaches to improve detection of suspicious activity.

What you'll bring to the role?

• Master's or PhD degree in Computer Science, Machine Learning, Intelligent Systems, Statistics, Mathematics, Engineering or other highly quantitative fields
• 5+ years of hands‑on industry experience in building AI/ML/NLP solutions and applied statistical analysis to solve complex business problems
• Knowledge of software design and system principles and excellent skills in either Python (preferred) or Java
• Experience with AI/ML/NLP software packages such as LangChain, LangGraph, Semantic Kernel, CrewAI, OpenAI SDK, PyTorch, HuggingFace, etc.
• Experience in adhering to Software Development Life Cycle (SDLC) principles include GIT related operations
• Strong problem solving and time management skills
• Excellent written and oral communication skills
• Familiarity with financial markets, especially in Compliance, Non-Financial Risk, and Fraud analytics
• Experience with benchmark creation and evaluation including LLM-as-a-Judge based techniques
• Knowledge of Vector Stores, Linux, SPARQL, and Graph Databases

Typically, 8+ years' relevant experience would generally be expected to find the skills required for this role

Please note that the location listed for this role is temporary. The position’s work location will transition to 1445 Ross Ave, Dallas, TX 75202 at a future date. In-Person interviews will be required for the role.

WHAT YOU CAN EXPECT FROM MORGAN STANLEY:

At Morgan Stanley, we raise, manage and allocate capital for our clients – helping them reach their goals. We do it in a way that’s differentiated - and we’ve done that for 90 years. Our values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - aren’t just beliefs, they guide the decisions we make every day to do what's best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries. At Morgan Stanley, you’ll find an opportunity to work alongside the best and the brightest, in an environment where you are supported and empowered. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences. We are proud to support our employees and their families at every point along their work‑life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry. There’s also ample opportunity to move about the business for those who show passion and grit in their work.

To learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-offices into your browser.

Morgan Stanley is an equal opportunity employer committed to building and maintaining a workforce that is diverse in experience and background. Our recruiting efforts reflect our strong commitment to a culture of inclusion, where individuals are hired, developed, and advanced based on their skills and talents.

Our workforce reflects a broad cross-section of the global communities in which we operate, bringing a variety of backgrounds, talents, perspectives, and experiences.

For more information, please visit: https://www.morganstanley.com/people-opportunities/eeo.