NLP Scientist Career Guide
Natural language processing, abbreviated NLP, takes place when computers use artificial intelligence to understand human languages. As an NLP scientist, you will work to design and create machines that correctly understand patterns in human language. These same machines can also translate specific words into other spoken languages.
One of several modern careers that require a knowledge of machine learning, NLP scientists work toward a common goal: to create computers that can understand human languages as naturally as any human can. To accomplish this goal, NLP scientists routinely use a variety of programming languages and scripting to create machines and applications that integrate NLP into their functionality.
If you have a passion for coding or information technology, and are interested in learning how machines communicate with each other and with humans, a career as an NLP scientist is ideal for you.
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.
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.
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.
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.
Computer Science – B.S.
Problem solvers and math lovers needed! Your task: ...
Problem solvers and math lovers needed! Your...
Problem solvers and math lovers needed! Your task:
Lay the groundwork for the computing breakthroughs that will enable tomorrow's technologies.
- Time: 67% of graduates in similar programs finish within 30 months.
- Tuition and fees: $3,985 per 6-month term.
- Transfer: Your previous college coursework and existing certifications may waive course requirements, helping you finish even faster.
You'll have the opportunity to earn these certifications:
- Linux Essentials
- Axelos ITIL Foundation
Professionals who need the skills a computer science degree provides include computer systems analysts, computer programmers, artificial intelligence specialists, software engineers, machine learning engineers, and more.
No need to wait for spring or fall semester. It's back-to-school time at WGU year-round. Get started by talking to an Enrollment Counselor today, and you'll be on your way to realizing your dream of a bachelor's or master's degree—sooner than you might think!
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.
How Much Does an NLP Scientist Make?
The exact income of an NLP scientist varies depending on several factors. These factors include an NLP scientist's employer, employer location, years of experience, obtained certifications, and portfolio. In general, the salary of an NLP scientist averages $105,178 per year, with a range of roughly $78,000 to $139,000 per year.
What Is the Projected Job Growth?
Employment for NLP scientists—and all computer and information research scientists—is expected to see growth of 22% from 2020 to 2030. This forecasted expansion rate is extremely high, well above the average for all occupations across the board. As NLP applications continue to become more common in personal and professional software programs, NLP scientists will see their role become even more important.
Do NLP Scientists Need Certification?
Before you can become an NLP scientist, some employers require that you obtain one or more related certifications. Certifications useful to an NLP scientist include:
-ITIL® Foundation Certification
These and other IT certifications allow NLP scientists to fulfill their positions to a greater extent.