Computational linguist jobs & Careers




What is a Computational Linguist?

A computational linguist is a professional who combines knowledge of linguistics, computer science, and artificial intelligence to develop computer programs that can understand human language. These professionals help in developing natural language processing (NLP) systems that enable computer programs to understand, interpret, and generate human language. Computational linguists are in high demand in industries such as healthcare, education, finance, and technology.

What usually do in this position?

As a computational linguist, your primary role is to develop NLP systems that can process and understand human language. You will need to analyze language data, develop algorithms, and implement machine learning models to create effective NLP systems. You will be responsible for designing, testing, and improving NLP models to ensure that they can accurately interpret and generate human language. Additionally, you may be required to collaborate with other professionals such as software developers, data scientists, and product managers to ensure that the NLP system meets the business needs.

Top 5 skills for the position

  • Strong knowledge of linguistics, computer science, and artificial intelligence
  • Expertise in programming languages such as Python and Java
  • Experience in developing NLP models using machine learning algorithms
  • Excellent analytical and problem-solving skills
  • Strong communication and collaboration skills

How to become a Computational Linguist?

To become a computational linguist, you need to have a strong foundation in linguistics, computer science, and artificial intelligence. A bachelor's degree in computer science, linguistics, or a related field is typically required, although some employers may prefer candidates with a master's degree or Ph.D. in a related field. Additionally, you will need to have experience in programming languages such as Python and Java and have expertise in developing NLP models using machine learning algorithms. You may also need to complete certification programs in NLP and machine learning to further enhance your skills.

Average Salary

According to Glassdoor, the average salary for a computational linguist in the United States is $108,000 per year. However, this can vary depending on factors such as experience, location, and industry.

Roles and Types

Computational linguists can work in a variety of roles and industries. Some common roles include NLP engineer, data scientist, software developer, and research scientist. Industries that typically employ computational linguists include healthcare, education, finance, and technology. Additionally, there are different types of NLP systems that computational linguists can work on, including sentiment analysis, speech recognition, and machine translation.

Locations with the Most Popular Jobs in USA

Some of the top locations for computational linguist jobs in the United States include San Francisco, New York, Seattle, Boston, and Washington D.C. These cities are home to some of the largest technology companies and research institutions, making them ideal for professionals looking to work in this field.

What are the Typical Tools?

Computational linguists use a variety of tools to develop NLP systems, including programming languages such as Python and Java, machine learning frameworks such as Tensorflow and PyTorch, and NLP libraries such as NLTK and SpaCy. Additionally, they may use data visualization tools such as Tableau and PowerBI to analyze language data and present their findings to stakeholders.

In Conclusion

Computational linguistics is an exciting and rapidly growing field that offers a range of career opportunities for professionals with a strong foundation in linguistics, computer science, and artificial intelligence. With the increasing demand for NLP systems in various industries, the role of a computational linguist has become more critical than ever. If you are interested in pursuing a career in this field, it is essential to develop expertise in programming languages, machine learning algorithms, and NLP libraries to succeed in this exciting and challenging field.