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Nlp Finance Jobs (NOW HIRING)

Lead Data Scientist

Manhattan, NY · On-site

$166 - $214/hr

Summary As a Lead Data Scientist (NLP & Financial Compliance) at Smarsh , you will spearhead the development of state‑of‑the‑art natural language processing (NLP) and large language model (LLM ...

Lead Data Scientist

Atlanta, GA · Remote

$166K - $214K/yr

Summary As a Lead Data Scientist (NLP & Financial Compliance) at Smarsh , you will spearhead the development of state-of-the-art natural language processing (NLP) and large language model (LLM ...

OR · On-site

Summary As a Lead Data Scientist (NLP & Financial Compliance) at Smarsh , you will spearhead the development of state-of-the-art natural language processing (NLP) and large language model (LLM ...

Summary As a Lead Data Scientist (NLP & Financial Compliance) at Smarsh , you will spearhead the development of state-of-the-art natural language processing (NLP) and large language model (LLM ...

Summary As a Lead Data Scientist (NLP & Financial Compliance) at Smarsh , you will spearhead the development of state-of-the-art natural language processing (NLP) and large language model (LLM ...

Lead Data Scientist

OR · Remote

$166K - $214K/yr

Summary As a Lead Data Scientist (NLP & Financial Compliance) at Smarsh , you will spearhead the development of state-of-the-art natural language processing (NLP) and large language model (LLM ...

Summary As a Lead Data Scientist (NLP & Financial Compliance) at Smarsh , you will spearhead the development of state-of-the-art natural language processing (NLP) and large language model (LLM ...

Summary As a Lead Data Scientist (NLP & Financial Compliance) at Smarsh , you will spearhead the development of state-of-the-art natural language processing (NLP) and large language model (LLM ...

Showing results 21-40

Nlp Finance information

See salary details

$37.5K

$122.7K

$196.5K

How much do nlp finance jobs pay per year?

As of Aug 8, 2026, the average yearly pay for nlp finance in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is NLP Finance?

NLP Finance refers to the application of Natural Language Processing (NLP) techniques in the financial industry. NLP is a branch of artificial intelligence that focuses on the interaction between computers and human language. In finance, NLP is used to analyze financial documents, news, social media, and other text data to extract insights, detect trends, and automate processes such as sentiment analysis, risk assessment, and fraud detection. This helps financial institutions make more informed decisions and improve operational efficiency.

What are the key skills and qualifications needed to thrive as an NLP Finance specialist?

To thrive as an NLP Finance Specialist, you need strong expertise in natural language processing, machine learning, and financial data analysis, typically supported by a degree in computer science, data science, or a related field. Proficiency with programming languages like Python, NLP libraries (such as spaCy, NLTK, or Hugging Face), and experience with financial data platforms and APIs are essential. Excellent problem-solving, analytical thinking, and communication skills help you interpret complex financial data and collaborate with stakeholders. These skills are crucial for developing reliable NLP solutions that extract insights from financial texts, driving better decision-making in a fast-paced industry.

How does an NLP Finance professional typically collaborate with data scientists and financial analysts on projects?

NLP Finance professionals often work closely with data scientists and financial analysts to develop models that extract insights from unstructured financial data, such as earnings calls, news articles, and reports. They contribute their expertise in natural language processing by designing algorithms and tools that make this data more accessible and actionable for the team. Effective collaboration usually involves regular meetings to align on project goals, sharing domain-specific knowledge, and integrating NLP outputs into broader financial models or dashboards. Clear communication and a strong understanding of both finance and NLP methodologies are key to successful teamwork in this role.

What is the difference between Nlp Finance vs Data Analyst?

AspectNlp FinanceData Analyst
Required CredentialsDegree in Finance, Computer Science, or related fields; knowledge of NLP toolsBachelor's or higher in Statistics, Mathematics, or related fields; proficiency in data analysis tools
Work EnvironmentFinancial institutions, tech companies, or consulting firms focusing on financial dataVarious industries including finance, healthcare, marketing, often in office settings
Employer & Industry UsageFinance firms leveraging NLP for sentiment analysis, risk assessmentOrganizations analyzing large datasets to inform business decisions across sectors

While both roles involve data analysis skills, Nlp Finance specializes in applying natural language processing techniques to financial data, whereas Data Analysts work broadly across industries analyzing diverse datasets. Nlp Finance professionals focus on language-based data within finance, making their expertise more niche compared to the generalist role of Data Analysts.

What cities are hiring for Nlp Finance jobs? Cities with the most Nlp Finance job openings:
What states have the most Nlp Finance jobs? States with the most job openings for Nlp Finance jobs include:
Infographic showing various Nlp Finance job openings in the United States as of August 2026, with employment types broken down into 80% Full Time, and 20% Part Time. Highlights an 80% In-person, and 20% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Data Scientist (NLP and GenAI Specialist)

Morgan Stanley

Dallas, TX • On-site

Full-time

Re-posted 9 days ago


Morgan Stanley rating

8.4

Company rating: 8.4 out of 10

Based on 155 frontline employees who took The Breakroom Quiz

30th of 150 rated financial services


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
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.

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