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Data Scientist (NLP and GenAI Specialist)

Reads like a ML Engineer role: putting models into production.

Dallas, TX, US; Austin, TX, US; Houston, TX, US; San Antonio, TX, US

Open 3 months, first seen by us 99 days ago
Pay
Pay not listedSimilar roles state $166K–$240K
Work setting
Not stated
Employment
Temporary · Full-time — employment source
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:
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting

What you’ll work on

Full posting
  • Design AI systems using LLMs, RAG, agentic AI and knowledge graphs

  • Build GenAI solutions that automate manual compliance tasks

  • Research new methods to improve analytical solutions

  • Work with Compliance, Legal, Financial Crimes and IT on AI adoption

  • Improve detection of suspicious activity

From the employer’s posting
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.
Education & alternatives
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

Tools in this posting

  • Java
  • Python
  • Hugging Face
  • PyTorch
Source — Tool mentions in context
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

Posting record

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Open 3 monthsWe first saw this posting 99 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records
Live
First seen by us
Jul 29, 202699 days ago
Recorded sightings
204
Last seen by us
Nov 5, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$166K–$240K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 1,279 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 99

Up longer than most. Similar jobs usually come down between day 6 and day 70.

Well past Morgan Stanley’s usual: its jobs come down by about day 31.

From 4,444 similar postings that came down, and 183 of Morgan Stanley’s. Coming down is not always a hire.

Morgan Stanley is hiring

48 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring has slowed
  • Takes jobs down at a usual pace
  • 2% of open jobs were reposted
Hiring record

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Has Morgan Stanley posted this job before?

Yes. We’ve followed 2 other Data Scientist (NLP and GenAI Specialist) jobs there since May 2026. 2 came down, usually after about 55 days.

  1. Place not statedCame down after 55 days, first seen May 12
  2. BudapestCame down after 55 days, first seen May 12
  3. This jobUp 99 days so far, first seen Jul 29

About Morgan Stanley

People
About 83,000 in 2025.Annual report (SEC Form 10-K)
Company
Listed as MS.

Demand for ML Engineer roles

New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.

Weekly new ML Engineer postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 625, the most 1,094, and the latest week had 876.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

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.
Source details

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Pay

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Location & working pattern

Dallas, TX, US; Austin, TX, US; Houston, TX, US; San Antonio, TX, US

Working pattern and location restrictions need checking in the full posting.

Work authorization

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