OVERVIEW
What Is a Natural Language Processing (NLP) Scientist?
An NLP scientist is responsible for the technical creation and coding of NLP devices and applications. Ultimately, these professionals provide machines with the ability to understand human languages. Whether an NLP scientist is responsible for the development of a physical device or a mobile application, their project will require the integration of a system that understands human vocabulary.
Programs like Duolingo and Google Assistant represent the increasing value of NLP programs, which can integrate natural language processing capabilities into AI applications. In addition, website chatbots have seen a recent rise in popularity, helping customers satisfy common online concerns without the need for a live representative.
NLP applications are also useful in offering predictive text features. Predictive text programs are used to forecast what technology users are thinking and recommend corresponding text. For example, predictive text features are already used in email correspondence and text messaging to help users save time.
NLP scientists benefit from undergraduate degrees in computer-related fields, alongside a variety of certifications that improve their proficiency in specific programming languages. In addition, many NLP scientists also benefit from experience with the devices or applications to receive NLP technology.
RESPONSIBILITIES
What Does an NLP Scientist Do?
As an NLP scientist, you could potentially work in a variety of different locations. These specific places of employment may include:
- Your client’s place of business
- Machine learning and robotics companies
- Universities or institutions of higher learning
- Research firms
- Financial institutions
- Technology investors
The location of your office will often depend on your employer, and the nature of your employment. If you work on behalf of a firm, you might find yourself traveling to and from a client’s place of business. Alternatively, NLP scientists hired by private companies will likely spend the majority of their time working in their own offices.
On a day-to-day basis, an NLP scientist can fulfill a wide variety of tasks. While working to create programs that understand human language, NLP scientists will often interact with other team members, manipulate programming languages, and solve technology-related problems.
The specific responsibilities of an NLP scientist may include:
- Designing NLP systems for integration into physical devices, software programs, mobile platforms, and other applications.
- Implementing advanced algorithms into NLP systems, according to client specifications or project needs.
- Using effective text representation strategies, allowing NLP systems to understand the specific diction that makes up human language.
- Running evaluation experiments on NLP systems during the creation process to gauge how well the systems adapt to and understand the specifics of human language.
- Accounting for specific speech patterns that might affect how well an NLP system understands language.
- Reporting regular NLP system updates to team members, company executives, and clients.
These and other responsibilities define the daily tasks of an NLP scientist.
EDUCATION & BEST DEGREES
What Education Does an NLP Scientist Need?
If you’re looking to become an NLP scientist, you will first need to satisfy basic education requirements. These include a bachelor’s degree in computer science or a closely-related technological field, where you’ll develop skills in systems architecture, computer logic, data structures, artificial intelligence, and other useful fields.
This degree will teach you skills that are of immediate use to NLP scientists as you grow more familiar with modern analytics tools like Python, SQL, and Tableau.
Best Degrees for an NLP Scientist
Technology
AI Engineering - B.S.
Earn your bachelor’s degree in AI engineering and learn to build the...
Earn your bachelor’s degree in AI engineering and learn to build the skills needed to design, deploy, and operate AI systems in production, combining software engineering, machine learning, and cloud infrastructure.
- Time: Approximately 4 years
- Tuition: $4,200 per 6-month term.
- Courses: 40 total courses in this program.
Certifications included in this program at no additional cost:
- Microsoft Certified: Azure AI Fundamentals
Skills for your résumé you will learn in this program include:
- AI deployment and Integration
- AI workflow automation
- AI security and risk management
- AI application development
- Programming (Python, C#, SQL)
Technology
Computer Science – B.S.
ABET-accredited. AI-focused. Computer science that counts....
ABET-accredited. AI-focused. Computer science that counts.
Lay the groundwork for the computing breakthroughs that will enable tomorrow's technologies. Utilize your previous college courses or IT experience to help you complete your degree faster.
- Time: 62% of graduates in similar programs finish within 25 months.
- Tuition: $4,125 per 6-month term.
- Courses: 37 total courses in this program.
You'll have the opportunity to earn these certifications:
- Linux Essentials
- Axelos ITIL Foundation
You can also accelerate your program and complete both a B.S. in Computer Science and an M.S. in Computer Science together, requiring less courses overall and saving you time and money. Learn more about this option.
Skills for your résumé that you will learn in this program:
- Artifical Intelligence (AI)
- Machine Learning
- Logic
- Architecture and systems
- Data structures
- Computer theory
- Version Control
- Linux
Technology
Computer Science – M.S.
Harness AI. Drive innovation. Lead with a master's in computer science....
Harness AI. Drive innovation. Lead with a master's in computer science.
- Time: 61% of graduates finish similar programs within 20 months.
- Tuition: $4,385 per 6-month term.
- Courses: 10 total courses in this program.
The M.S. in Computer Science at WGU has three specializations for students to choose from, giving them the opportunity to focus on an area that is meaningful for their career and life. The specializations are Computing Systems, Human-Computer Interaction, and Machine Learning and Artificial Intelligence. You can also accelerate your program and complete both a B.S. in Computer Science and an M.S. in Computer Science together, requiring less courses overall and saving you time and money.
Skills for your résumé that you will learn in the computer science programs include:
- Programming and Logic
- Architecture and Systems
- Data Structures
- AI
- Project Management
How Much Does an NLP Scientist Make?
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According to Salary.com (as of July 1, 2025), the average annual salary for an NLP Scientist in the U.S. is (((nlp_scientist.averageSalary)))—about $60 per hour. Most professionals earn between $98,419 (10th percentile) and $142,809 (90th percentile), with the majority falling between $110,952 (25th) and $134,188 (75th percentile).
What Is the Projected Job Growth?
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Although the Bureau of Labor Statistics does not report specific job growth for NLP Scientists, this role is closely aligned with Computer and Information Research Scientists—a category projected to grow by (((nlp_scientist.jobGrowth))) from 2023 to 2033. This "much faster than average" growth reflects surging demand driven by advancements in AI, machine learning, and language technologies.
SKILLS
What Skills Does an NLP Scientist Need?
NLP scientists depend on a portfolio of skills to succeed on the job. These skills help them develop applications, collaborate with team members, and solve problems that might arise in their work environment.
Daily, the skills an NLP scientist uses can include:
- Text representation technique implementation: The ability to associate meaning with individual words in an NLP system.
- Teamwork: The ability to work well alongside other NLP scientists, data scientists, programmers, and clients to develop systems that meet project benchmarks.
- Problem-solving: The ability to address and creatively solve issues that NLP systems are likely to face in design and development.
- Programming: The ability to implement a working knowledge of Python, Java, and other coding languages during the NLP-systems creation process.
- Software design: The ability to expertly create software programs that leverage semantic extraction techniques to fulfill NLP requirements.
- Code troubleshooting: The ability to test and troubleshoot code, eliminating any bugs in programming languages before systems are approved.
These and other skills allow NLP scientists to fulfill the core responsibilities of their job while working well alongside fellow team members.
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