Data Scientist (NLP and GenAI Specialist)

Morgan Stanley•Dallas, TX

About The Position

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.

Requirements

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

Responsibilities

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.