Linguistics Jobs: Interview with a Natural Language Annotation Lead
This month’s Linguistics Job Series interview is with Hadas Kotek, who works as a Natural Language Annotation Lead. Hadas previously worked in academia before transitioning to the tech industry, a move she recounts in detail in this interview. Moving away from academia can be a nerve-wracking adjustment, and in this post Hadas gives her advice to those considering pursuing roles in industry and shares her experience from applying to jobs to accepting an offer for her current role at Apple.
You can follow Hadas on Twitter (@HadasKotek) and on LinkedIn.
What did you study at university?
I double-majored in linguistics and political science at Tel-Aviv University. I took some additional courses in mathematics and computer science but never completed a degree in either one. I got a PhD is in linguistics from MIT. My focus was on theoretical syntax and semantics but there was also an experimental component to my research. I then had several non-tenure-track teaching positions in syntax and semantics after I graduated.
What is your job?
My responsibilities as a Natural Language Annotation Lead have changed over the last few years. Initially, I spent a lot of time on project management: setting project priorities for teams, creating guidelines, tracking project progress, facilitating communication between engineers and annotators, etc. In other quarters, I’ve worked on ontology development. Most recently, I’ve been growing more in the data science direction, with a focus on annotation efficiency and quality.
How does your linguistics training help you in your job?
There are various aspects of my training as a linguist and as a professor that have helped me tremendously. First, the ability to explain simple linguistic concepts with examples off the top of my head, as I would in an Introduction to Linguistics lecture. Second, the ability to teach diverse audiences and to present complex concepts and results in a concise manner. Third, the ability to think in generalizations—this is a superpower linguists possess that they should appreciate more! Knowing basic typological facts about various languages has also been helpful in my job. In addition, the quantitative aspects of my research, specifically the ability to design behavioral studies and to engage in data visualization and statistical analysis, have come in handy. Being proficient in a scripting language (R which I used previously in experimental work, and now python), is also obviously helpful.
In fact, I would say the main thing that wasn’t directly helpful (although it didn’t hurt, either) is the detailed content of my work: my academic research is in the area of A-bar syntax and semantics, including wh-questions, focus, and ellipsis, and (at least thus far), I can’t say that the cutting edge theories I developed or learned have furthered my work in any way (but, who knows, maybe one day I’ll get to discuss the finer points of covert movement, islands, and focus alternatives with some curious engineering team!).
What was the transition from university to work like for you?
There were two main parts to my transition out of academia. First, a longer and slower phase of coming to terms with the decision, which wasn’t easy at all. I would describe it as a grieving process for what could have been. This was also the discovery phase, where I connected with some friends and acquaintances who had made the move into industry earlier. I had a lot of questions and knew very little when I started: what kinds of jobs are out there, what skills do I have that are desirable, where are companies located, how do I find job ads, what the interview process is like, what I should expect for compensation, to name a few. None of this was covered when I was in grad school or later at any institution I was teaching at. I was fortunate to have some friends who were willing to take the time to answer my questions and also tell me some things I wouldn’t have even thought to ask. They also helped me with my resume, sent me job ads, and submitted referrals for me when they could, which was truly invaluable. I did most of this work in the fall semester of the year I left academia.
The second phase was the active job search. That went exceptionally quickly and successfully for me, more than I think is the norm. I started by applying to a single job that ticked all the boxes for what I wanted. I got as far as the on-site interview but didn’t get an offer. That took about one month. I then applied to about a half-dozen other jobs that ticked almost all of the boxes. This round took another month, and I ended it with three offers, and was able to pick the one that made the most sense in terms of job description and team. I also had offers for roles with the titles “ontologist” and “computational linguist”. Within another two months, I had moved across the country and started the job.
One of the reasons I preferred the job I took was that there was clear support to help me get started. That was important, as there’s a lot to learn in the beginning. The pace, the terminology, the day-to-day routines, are all different. I would say it took me about six months to feel like I understood what I was doing. And like I said in a previous answer, it’s been a growing process ever since, changing focus areas on the job and learning new skills. It was also a longer process to understand how to use my linguistic training in my work and to establish myself as a go-to expert in this area. If you have the right team and manager, you can do a lot to shape your own experience and maybe take the work in directions that both you and they would not have envisioned at the outset. Generally speaking, whenever I’ve pointed out relevant expertise I could bring to the table, it’s been embraced by my manager and given the attention it deserves.
Do you have any advice do you wish someone had given to you about linguistics/careers/university?
There are so many options out there. And not everything requires coding! It’s important when you get started to take the time to learn and understand what is available and to really think about what skills you enjoy using and would want to emphasize. If coding isn’t your thing, some basic knowledge could still be useful, but do you really want a full-time coding job where you’d be competing with people who are both more experienced than you and actually enjoy doing the work? Wouldn’t it be better to find roles that play to your strengths, where you’d really shine?
At the same time, because there are so many options, any single action and decision is less consequential. To explain what I mean: in academia, you generally strive for exactly one thing, namely a tenure-track position, which in time – often a long time – will lead to a permanent tenured position. Most people will have exactly one job for life, maybe two. Outside academia, the pace is different. You’ll move from job to job fairly frequently. This means that you can change focus over time, and the team you are on now is just one of several you’ll work on. If you don’t like the team or conditions or content of one job, you can always move to something else. You’re not locked into one single path just because you made one decision now. This may seem daunting, and it’s certainly a different pace than academia. Maybe it sounds like less job security; this is certainly what I thought. Now I think in terms of career security instead: there will always be other opportunities out there.
I would recommend thinking about this topic with some regularity and planning accordingly, especially if you still have some years left before you graduate. If you want to consider jobs that require coding or data science, then building some relevant coursework and projects into your work early on would be wise. If you’re into project management, find yourself things to organize or collaborations to lead. If you’re considering UX, figure out what you’d need to do to build a portfolio. Regardless of your direction, it’s very helpful to seek practical experience in the form of internships.
There’s also some common advice that is very true: spend the time learning and understanding what’s out there. Build your network. Understand your skills and their value. Learn the terminology of your new chosen field and understand how to translate your academic experience into this new language. Refine your resume. Start thinking of yourself as a “language specialist” or “linguist” or “(behavioral) scientist”, for example, rather than a “syntactician” or “sociophonetician” or any other narrow definition. Start out broadly and define the parameters of the job that matter most to you. When I got started, a friend told me that I had to answer three questions: (a) what do you want to do? (b) where do you want to live? (c) how much do you want to make?. The third question, especially, was hard for me to wrap my head around. But it was very useful in understanding how to approach a non-academic job search.
Any other thoughts or comments?
Network network network. It’s so important to make those connections. There are more opportunities now than probably at any time in the past. Grad schools are starting to understand that they need to support diverse career paths, and there are more and more materials out there that you can learn from, both online and in person. If your school isn’t inviting outside speakers to discuss career paths and how to prepare for them, you should be asking for that content! You’ll find that a lot of people are very generous with their time.
You can define your own path, and success can take on many different meanings over time and across individuals. Finally: academia can have a very narrow view. But despite common narratives, getting a non-academic job isn’t failure, unless you think that a fulfilling, well-paid job with lots of freedom to grow is somehow a negative. (It’s not!)
Related interviews:
Interview with a Senior Analyst, Strategic Insights & Analytics
Interview with a Data Scientist
Interview with a User Experience (UX) Researcher
Interview with a Computational Linguist
Recent interviews:
Interview with an EMLS/Linguistics instructor & mother of four
Interview with a Performing Artiste and Freelance Editor
Interview with a Customer Success Manager
Interview with an Impact Lead
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Resources:
The full Linguist Jobs Interview List
The Linguist Jobs tag for the most recent interviews
The Linguistics Jobs slide deck (overview, resources and activities)
The Linguistics Jobs Interview series is edited by Martha Tsutsui Billins. Martha is a linguist whose research focuses on the Ryukyuan language Amami Oshima, specifically honourifics and politeness strategies in the context of language endangerment. Martha runs Field Notes, a podcast about linguistic fieldwork.
