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Job titles and job descriptions for linguists (and other social scientists)

Jan 3, 2023

If you studied engineering or computer science or another STEM field, several career-related first steps would be easy for you. For one, it’s clear what the transferable skills from your education might be. Job ads will explicitly list your degree in their ‘education’ field. Job titles are relatively streamlined and straightforward. And it’s assumed and expected that many in your cohort will get industry jobs upon graduation. There are resources and existing knowledge in your institution to help students find those jobs; it’s certainly not considered a failure or exception of some kind.

Not so if you’re a linguist (or other social scientist).

Preamble: about this post

For linguists, relevant industry job titles can be entirely non-obvious. Unlike in academia, where the only job you are taught to want is Assistant Professor, with a career path taking you to Associate Professor and perhaps Full Professor, outside academia, employers can use whatever title they want for their jobs. Therefore,

The same title could mean different things at different companies
The same job responsibilities can be called different names at different companies

Identifying the relevant skills you’ve learned in grad school can be a long journey. And once you’ve identified some potential jobs of interest, figuring out what they’re actually called is yet another journey.

This post is a summary of an extensive crowd-supported effort to collect the many types of jobs that are available to linguists (and other social scientists) along with descriptions from former academics who hold them. Since it’s a long post, I’ve done the following:

organized the job titles by category¹
included a (non-exhaustive) list of job titles that have similar or overlapping responsibilities
included some informal descriptions of the job responsibilities from people who hold those jobs²
included links to some archived job postings so you can get a sense for what job ads for these titles look like³

You may have also already encountered Superlinguo’s Linguist Job Interviews, which is an excellent resource that showcases linguists with diverse career paths and job titles. I’ll add a few links throughout this post but there are more, which you may want to browse as well (there’s even an interview with me!).

Finally, as always, a set of caveats goes here. The post will be long but not exhaustive. The categories are made up by me and there are some inevitable overlaps among them. My focus is more on the tech industry than other sectors, and has a linguistics/social science perspective and US focus. The sample job ads are simply what I happened to find, not an indication of where jobs are generally most likely to be found and certainly not an endorsement of the jobs themselves or the companies/sectors they are in. YMMV.

Language data roles

This is a broad category that includes what are perhaps the most obvious job titles for linguists. Even here, though, most job titles actually aren’t linguist. In fact, most jobs with the title “linguist” tend to be translation-related, and not what linguistics PhDs are trained to do. I’m including all jobs in this category that engage with data for machine learning in all its aspects from annotation to data science to training models.

Less technical: analytical linguist and variants

Work with the data that is used to train machine-learning models at various stages of the process and/or with the people who annotate the data. May require some technical skills (mostly data analysis or SQL). Most jobs are at tech companies.

Some job titles: Linguist, Analytical linguist, Computational Linguist, Principal Computational Linguist, AI Linguist, Technical Linguist, Language Engineer, Language Data Researcher, Data Specialist, Product Operations Manager, Annotation Project Lead.

Some informal descriptions of job responsibilities:

“Anything touching data in the NLP space. Deciding what data to collect, how, how to annotate and evaluate it, how to evaluate systems that use it. At higher levels, identifying data that needs to be analyzed that currently isn’t.”

“Design, run, prioritize, and generally own everything about annotation projects. Create annotation guidelines, create and maintain the ontologies used in annotation, create trainings, answer annotator questions, provide ongoing feedback to annotators to improve their work, propose ways to improve the tasks to improve the speed and accuracy of the overall process.”

“Collecting and improving datasets for training and evaluation, developing/improving evaluation methods, and sometimes going over the results of an evaluation to identify areas where a system can improve, etc.”

“Many ALs find themselves doing things like project management and technical writing for a limited stretch of time, even if it’s not their core job description”

Some links to job ads:

Some interview links:

More technical: data science and variants

Work with annotated data to train machine-learning models and/or analyze their results. Usually requires an understanding of NLP and AI/ML tools and/or as data analysis methods.

Some job titles: Data Analyst, Data Scientist, Data Science Analyst, Search Quality Analyst, Language Analyst, NLP engineer, Language Engineer, Computational Linguist, Conversational AI Engineer, Applied Scientist, NLP Scientist, Localization Engineer

Some informal descriptions of job responsibilities:

“Experimental design + testing, data visualization, modeling, setting up + monitoring data pipelines, thinking through strategy, setting/tracking goals/metrics, and explaining all of the above to other people.”

“Analyzing the problem, figuring out the best architecture to solve it, sometimes some data annotation, then writing code to pre-process your data and to either train a model or use an existing model, then analysing the performance of the model/figuring out ways to improve it.”

“Prototyping current deep learning and other machine learning techniques in natural language processing and computer vision, to develop solutions in applied problem areas.”

Some links to job ads:

Some interview links:

Most technical – developers and engineers

There are, of course, also language-related roles that are basically engineering roles. You can be a software engineer, full-stack/front end/back end developer, NLP engineer, AIML researcher/scientist, and similar. These would be roles that require high competency in coding and the latest AIML techniques. You can already see some of that in the links above. I won’t go into additional details here.

And, of course, there are also lots of data-related roles that aren’t language related, but again this post is going to be long enough without trying to exhaustively list those roles, too.

Some interview links:

Superlinguo Interview with a Software Engineer (Brooke Lynne Weaver)

Caveat

The grouping I made here is somewhat artificial. As I hope the descriptions make clear, the actual set of responsibilities you might have could fall anywhere along the spectrum of {creating guidelines, doing trainings, giving feedback to annotators} > {designing annotation projects, devising data strategies, doing data sampling, constructing and running projects} > {analyzing results of projects, doing error analysis, tracking metrics} > {training ML models, devising and using evaluation methods, building products that use the models}.

In fact, a team of linguists could have several members with the same title (say, Analytical Linguist at Google) but each person could be in charge of different aspects of the process for different projects or at different times. You’ll have to read the job ad and talk to the recruiter and hiring manager to know how technical a particular job is and whether it suits your skills.

An aside: annotation

The jobs I described above often involve supervising or working with data produced through annotation.

The people who engage in annotation could be linguists and the data itself could be language related, but for the most part PhDs are over-qualified for this role.⁵ Broadly, annotation jobs involve assigning labels to data or evaluating the quality of data. For example, you may be shown an ad and asked if it’s related to a search query, or you may be shown a search query and asked what category (out of a predetermined list) it belongs to. Annotation jobs tend to be hourly contract roles that aren’t particularly well paid, but as always there are exceptions to this rule.

Job titles will include keywords like: labeler, annotator, rater, grader, analyst, tester, data specialist.

Some links to job ads:

Knowledge engineering

Create ontologies/taxonomies, develop annotation schemas, define the label space used for annotation for machine-learning products.

Some job titles: Knowledge Engineer, Ontologist, Taxonomist, Information Manager, Content Manager, Content Strategist, Content Specialist, Product Hierarchy Specialist, Vocabulary Prototyping Associate, Vocabulary Engineering Associate, Lexical Developer

Some informal descriptions of job responsibilities:

“Managing metadata to help organize data like shopping inventories, medical data, etc.”

“Responsible for ensuring products are assigned to the correct taxonomy. This is relevant for retailers and brands who want to see their sales reports by product category and need to make sure therefore that products are classified correctly.”

“My company has lots of searchable data. My job is to make sure that all the data is properly tagged and organized so that it can be accessed easily. We also make our data available to technologies like Siri and Amazon Alexa, so part of this tagging involves writing code that can interpret natural language queries. Since we only have a finite set of data, this code is closer to computational sentence diagramming and writing generative grammar rules than it is to machine learning.”

“My role is a combination of ontological design + data analytics + product management.”

Some links to job ads:

Some interview links:

Superlinguo Interview with a Metadata Specialist and Genealogist (Mallory Manley)

Research

A lot can go into here. I’m going to separate out UX research from the rest simply because I have a lot of descriptions from people in those roles. Once again, this is a fully artificial split that I’m making just for convenience.

General roles

Use qualitative and/or quantitative tools (A/B testing, interviews, questionnaires, data analysis, etc) to investigate how consumers and clients benefit from a product, what new features the market wants, what products exist in the market and how makes each one unique, how to make products friendly, how to increase customer satisfaction, how to improve employee retention, etc. Create reports and presentations to share findings with clients and internal stakeholders.

Some job titles: Research Analyst, Research Scientist, Research-Innovation Lead, Solutions Innovator, Insights Consultant, Marketing Researcher, Ethnographic Researcher, People Analytics Specialist, Behavioral Scientist, Applied Scientist, Data Quality Curator, Researcher, Growth Strategist, Chief Learning Officer, Chief Knowledge Officer, R&D (research & development).

Some informal descriptions of job responsibilities:

“I design and carry out ethnographic research projects using a variety of qualitative methods (focus groups, surveys, participant observation, etc.) to study and improve guest experiences at a theme park.”

“As a Marketing Researcher I conduct business-to-business (B2B) and consumer-focused surveys to gauge brand and consumer needs and pain points, with an eye towards highlighting how my company’s products uniquely solve the pain points. I draw insights to support sales & marketing”

“I work to help clients better understand their customer’s pain points and improve their marketing/product design to promote growth.”

“I conduct research in education, psychology and neuroscience fields in order to develop products that can improve learning and build competencies for industry talents.”

“I connect up research teams with commercial product and service teams at an ethical AI company.”

“I do basic science research on speech production adaptation and dementia.”

“I supervise a team of researchers engaged in studies related to language learning and its importance in our multilingual world, as well as program evaluation for large-scale language learning and teacher training programs.”

Some links to job ads:

Some interview links:

User experience and design, conversation design

Do research and/or design that focuses specifically on the user. This can include work with voice-centric products or with other products.

Some job titles: UX Researcher, Human Factors Engineer, Content Designer, Content Strategist, UX writer, UX Design, Conversation Designer, Voice Designer, Voice-User Interface Designer, Conversational Architect, Chatbot Designer

Some informal descriptions of job responsibilities:

“I do quantitative behavioral/attitudinal human subjects research to evaluate how people use, perceive, and experience novel audio tech”

“I map out the interaction model for new features on my assistant product. I advocate for UX in the face of technical constraints: what our voice assistant says and doesn’t say (+ the how! literally writing nlg templates), and brainstorm what Assistant should say (guidelines)”

“I design how interactions could/should work for various companies, and partner with engineers to make it happen.”

“I was a consultant who did both user experience research and human factors research, which are related but not the same. HF often focuses on physical products and ergonomics, so you would work with folks with advanced degrees in ergonomics, but the general process of HF research and UX research is very similar. They both have to do with understanding the problem space, helping designers iterate on their concepts, and then validating the final solution before it gets handed off to engineering/development to make the final product. Mostly qualitative, but did do some mixed methods research.”

“UXRs conduct end-to-end research in the product lifecycle, which means they do foundational research to understand the problem space, they do concept testing in partnership with product designers and product managers, and then validate final designs with usability studies before they go to developers/engineering to be built/shipped.”

“Content designers/strategists partner closely with product designers and product managers during the development process to make sure the visual designs and content align to help users meet their goals. They can do anything from writing UX copy, communication emails to end users, and develop the whole messaging strategy for a feature. (e.g. how do we 1. Introduce the feature, 2. Communicate the value, 3. Write copy in the user interface that supports the user goal/task)”

Some job ads:

Some interview links:

Localization

Localization (l10n) or internationalization (i18n), often in combination with “language engineering” roles involve adapting a product that was created in language X (often but not always English) to another language or market. The simplest form involves translation of existing materials to the local language, but will often involve actually contributing new content that’s specifically relevant to the language, culture, and market.

Some job titles: Language Engineer, Localization Project Manager, Machine Translation Engineer, Translation Project Manager

Some informal descriptions of job responsibilities:

“Doing data collections for model testing, and localizing language artifacts for additional languages.”

Some links to job ads:

ProXXXX management

Drive different aspects of large-scale projects. Drive short- and long-term planning. Ensure projects are staffed appropriately and that budgets are met. Drive syncs and use organizational tools to report consistently on results and processes. Conduct retrospectives to learn from the past and plan better in the future. “Unblock” others, network within and across teams to identify needed resources to ensure progress.

Job titles (for once, this is fairly streamlined and easy to find): Product Manager, Program Manager, Project Manager, Engineering Project Manager, Technical Project Manager

Some links to job ads:

Some interview links:

Curriculum design

Create course content, timelines, and plans. Create metrics to evaluate learning outcomes. You might be employed by an EdTech company, by any other company that does internal trainings on its own (many large tech companies do this, for example), or by an academic institution.

There are also other teaching-related roles that fall outside the traditional academic TT path that might go here.

Some job titles: Curriculum Designer, Instructional Designer, Educational Developer, Test Developer

Some informal descriptions of job responsibilities:

“Create subject content (e.g. language arts, foreign language) and evaluate their effectiveness.”

“Create online course content as a part of a digital training session.”

“I work in a teaching and learning center where I support the campus community in the design, implementation, and evaluation of various learning experiences. I facilitate a lot of workshops and longer courses, most of which focus on eLearning, internationalization, and the scholarship of teaching and learning.”

“Worked with large-scale (statewide and nationwide) clients to develop equitable, reliable, multi-modal assessments of English language proficiency for students in K-12 settings. Supervised freelance test item writers, trained instructors on giving the test instrument, and supervised raters of student scores on qualitative assessments.

Some links to job ads:

Some interview links:

Work at academic institutions

There are many roles in academia that aren’t research-related, either on the tenure track or otherwise. There are teaching stream jobs, there are administration jobs such as Assistant Dean of students or Director of Postdoctoral Affairs. There are also options like librarian, course coordinator, office manager, etc. A list of titles would too long to exhaustively compile, but here are a few examples:

“Academic librarian (“Digital Scholarship Specialist”): I focus on text + data mining.”

“Subject librarian at a large university library: I maintain the collection for Linguistics, Dutch and German, give various skills trainings to students & researchers, and am one of the library’s Open Access specialists. Subject and liaison librarian for languages and literatures plus open access.”

“Director of Education and Professional Practice: I work at a professional association where I’m in charge of professional development, public / youth outreach and research on the profession. It’s mainly program management, service design and evaluation”

Some interview links:

Writing and editing

Various kinds of writing and editing-related jobs: Create documentation of materials developed by engineers and other content creators, work for a scientific publisher, do copywriting, or similar. This can happen at pretty much any institution, from government to corporate jobs to NGO to freelance.

Some job titles: Technical Writer, CI Writer, Document Designer, Lexicographer, Editor, Managing Director

Some informal descriptions of job responsibilities:

“write (along with many others) dictionaries (monolingual, bilingual, for learners,…); also involves specifications, usability & project management.”

“Content development and copywriting, social media, marketing, creating an arts & letters directory, currently working on a series of coffee table books on various languages.”

“work with some publisher to identify gaps or areas of growth and then identifies authors who might contribute content in those areas. Also reject or tweak unsolicited proposals – very few are ready to go as is”

“I run a scientific publisher; Typesetting, some scripting, some web programming, conference book stands, strategy, funding, accounting, PR, some staff development, some design and cartography.””

Some links to job ads:

Some interview links:

Diversity, Equity, and Inclusion

One particular use of a language background is in anti-bias, in the Diversity, Equity, and Inclusion (DEI) space. Two examples:

“Director, Anti-Bias Initiatives: I Collaborate with SEOs, marketers, editors, and journalists to improve brand health and safety. I integrate anti-bias editing into Content Integrity and DEI strategies company-wide. I train editors on inclusive and anti-bias editing.”

“Language Science and Design Manager Situated in DEI: I work with people both in DEI and language science/tech to develop frameworks and resources for identifying and working through bias in and about language.”

Some interview links:

Superlinguo Interview with a Language Revitalisation Program Director (Margaret Florey)

Various others

Each of the following sections could be expanded into its own category, but I don’t have enough expertise or information to do it on my own. If you know more about this, drop a comment with links or descriptions and I’ll try to expand the sections accordingly.

Science communication

Work with museums, libraries, government agencies, universities, private companies, NGOs, and other institutions, to communicate research findings with the general public.

Some interview links:

Naming, branding, advertising

Come up with brand names to best suit products, work with clients to research unique aspects of their brands.

Some interview links:

Operations (Ops)

Direct the logistical aspects of projects within your organization, including staffing, budgeting, hiring, prioritizing projects, procuring tools, evaluating efficiencies. Related to project management in some ways.

Quality Assurance

Develop or use metrics to check the accuracy and quality of products.

Freelance consulting, coaching, etc.

Build your own company! Do anything you want! There are no job ads here; the sky’s the limit.

A couple of examples:

“Transformational Coach: Through structured conversations held in a safe, confidential and non-judgemental space, I help clients overcome limiting beliefs as they navigate change to achieve their goals. I use a variety of techniques from psychology, UX, management, development and of course, linguistics. Key skill areas include deep listening, data analysis, conversation analysis, semantics, metaphor, pragmatics, and understanding of sociolinguistic principles. Also, research methods, esp qualitative and ethnographic approaches.”

“CEO of my own firm: Anti-bias consultant and researcher, book author, e-learning course creator/presenter.”

Some interview links:

Summary

This post was both long and non-exhaustive. There are so many opportunities out there. I realize that this may both exciting and intimidating at the same time. If you are not sure if you have enough experience to apply, I strongly encourage you to apply like Kyle!

Notes

I came up with the categories myself so take them with a grain of salt, but I think they’re useful at least for adding a bit of structure to this otherwise very long list. ↩
Descriptions all come from people who hold the relevant jobs and have a social science degree of some kind. Some descriptions are occasionally lightly edited for consistency and readability. ↩
These links are not meant to represent anything about availability or the sectors where these jobs are most likely to be found; they are simply illustrations of relevant job ads. In some cases it was not easy to find good examples (turns out the time between Christmas and New Year is not the best time to look); feel free to send more/better links my way, but please send archived links that won’t expire. ↩
At Amazon, in terms of technical skills required: Language Engineer (technical) > Language Data Researcher (analysis skills) > Data Specialist (non-technical), but linguists are routinely hired into all three roles. At other companies, “Language Engineer” might be reserved for a more programming-heavy role. ↩
It can still serve as a decent first job to get your foot in the door! I know several PhD linguists who started out as annotators and moved from there to a better paying FTE job. ↩

Hadas Kotek » Blog »

Job titles and job descriptions for linguists (and other social scientists)

Jan 3, 2023

Preamble: about this post

TOC

Language data roles

Less technical: analytical linguist and variants

More technical: data science and variants

Most technical – developers and engineers

Caveat

An aside: annotation

Knowledge engineering

Research

General roles

User experience and design, conversation design

Localization

ProXXXX management

Curriculum design

Work at academic institutions

Writing and editing

Diversity, Equity, and Inclusion

Various others

Science communication

Naming, branding, advertising

Operations (Ops)

Quality Assurance

Freelance consulting, coaching, etc.

Summary

Notes