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Hadas Kotek » Blog »

Prepping for Alt-Ac jobs (aka taking action)

Dec 29, 2022

So you’ve decided you want to explore non-academic jobs. You’ve also started to take some of the steps in Learning about Alt-Ac opportunities (aka how to get started) and have identified at least the beginnings of types of skills and jobs that might be of interest to you. This post discusses a few concrete steps you can take to get yourself started on the road toward a non-academic job.¹ As in other posts, I take a tech-focused approach since that’s where I am most knowledgeable, so YMMV.

Learn some coding

Starting from the most obvious, being able to code will open many doors for you in tech. Even if you’re not in a particularly technical role, it’s helpful to understand the basics. Do this if for no other reason than being able to code can help you get unblocked² where otherwise you might have to wait for someone else to do something for you. It will also help you communicate with engineers and other technical people in a language they understand.

If you’re not sure what to study, the two most common languages you might use are likely SQL and python.

SQL is a database querying language. At its core it allows you to join data tables, filter based on various criteria of interest, and perform basic operations on the results of the join. There are multiple online SQL courses you can take, and they should be more than enough for most jobs.³ SQL queries can get very fancy, but interviews will usually just want to see a basic familiarity.

Python is a scripting language. You’ll want to understand some basics like different types of loops, functions, and objects. Beyond that, it depends on what you might use it for — some options might include data analysis (e.g. using libraries like numpy,pandas, or csv), language processing (e.g. using libraries like nltk or spaCy), and data visualization (e.g. using matplotlib, seaborn, or plotly). Alternatively you might be more into model training (i.e. you’ll need to be familiar with scikitlearn, pytorch, or tensorflow).⁴

If you know R, learning python will require you to learn a new syntax to do things you mostly already know, which can be frustrating but is nonetheless entirely doable. Many jobs, especially on the more research side, may allow you to use R instead of python for your analyses, or they may even prefer it. (Or they may have in-house tools of their own.)

The level of proficiency you’ll need to obtain again depends on the kind of job you’ll want to have. You’ll need to be highly proficient to be a software engineer or ML engineer, and usually a lot less or none at all so be an analytical linguist or UX researcher, for example.

Learn some quantitative research methods

For me, the experimental experience I gained in grad school is by far the most directly applicable skillset that I use in my Alt-Ac career.

If you are in school and there is a lab in your department, consider joining it or trying out at least a project or two. Although it’s harder, you could also learn some of the following skills by yourself:

• Learn some stats
• Learn to design experimental studies, e.g. learn about factorial designs, randomization, considerations regarding project size, using distractor (or filler) items, how to design target and filler items, how to write instructions and create good practice items, etc.
• Learn about different methodologies and tasks from behavioral to physiological, for example large scale grammaticality surveys, speeded acceptability judgments, picture-matching, picture selection, reading time studies, eye-tracking, EEG, MEG, fMRI, etc.
• Learn to work with diverse study populations, such as speakers of different languages, children, cognitively impaired individuals, etc.
• Understand different types of response measures, e.g. binary answers, likert scales, slider scales, reading times, ERPs, etc.
• Understand how crowd workers (e.g. on Amazon Turk) engage with online surveys
• Understand how to interpret the results of experimental studies

You might accomplish some of this by taking relevant courses in your department, if they are available. You might pursue an independent study where you operationalize a theoretical question you’ve been working on and create an experiment based on it. Or you might join an existing project in a lab if you can identify such a project, so you can learn by observing as well as contributing.

In addition to direct learnings you will gain from such projects, you will also produce materials that could be useful in your future job search.

• A handout, slides, or written description of a study you are about to undertage (such as you might share with your advisor or a lab meeting) could be described as a design document.
• Guidelines you create for your studies are a type of document linguists routinely produce in the course of their job if they work with annotation or data analysis.
• You could consider hosting a version of a study you design on your personal website or on GitHub to showcase your skills to potential employers, along with your design documents and guidelines, data visualization of the results, and a short writeup of the main findings. Think of it as an entry in a portfolio.

Finally, to be a bit cynical but also realistic, it can be easier to obtain funding for experimental research than theoretical research sometimes. If you can find some small pots of money in the university or outside it, you could then add a relevant line to your resume about convincing stakeholders of the utility of your work and obtaining external funding.

Learn qualitative research methods

In addition to (or instead of, if it’s not your jam) quantitative methods, some jobs require diverse qualitative research skills. Some jobs are described as mixed methods or just straightforwardly as having a qualitative focus. Again, your university may offer courses or you may self-teach using online materials.

Here I want to stress that consultant work (aka fieldwork) should absolutely count as relevant experience. Whether you go out into the field or you work with native speakers in your office, you develop skills that can be used in non-academic settings.

You can think of an elicitation session as a semi-structured interview. That is, a situation where you come prepared with a set list of questions you’d like to have answered, but where you also allow the conversation to develop in unexpected directions based on what your consultant tells you. User studies often engage in a similar type of structure. In addition to the prep work that goes into a session, you learn to balance the need to get through your plan with the new paths your consultant might take you down, so you end up with maximally productive results. You also develop skills in recruiting consultants, working with different types of individuals (and groups), maintaining professional relationships, and learning how to interpret obvious and less obvious clues to understand what your consultant truly thinks. (For example, it’s not always easy to get a ‘no’ out of a consultant who may not wish to insult you, or you may discover how hard it is to work in a third language that is neither your nor your consultant’s native language, or you may have thoughts about the physical limitations of working in various field situations.)

Gain some managerial and organizational experience

Although everyone with a PhD is supposed to aspire to the coveted professor job at a top research institution, self-directed research — or even research at all — isn’t for everyone. Along the way in your grad program, you may have discovered that, in fact, you don’t want to always be chasing the next paper, writing the next grant, staying on top of the newest developments, or even telling others about them. That’s cool, research isn’t for everyone. There are jobs that use other parts of the skillset you developed in your grad program.

Do you enjoy organizing things, or laying out plans for others to execute? If so, there are jobs where you get to do that full time. Try to gain more experience along these lines.

For example, is there a way for you to have an undergraduate (or early grad) research assistant? This can happen in a lab setting where you mentor a younger lab member, or in some universities through directed program.⁵ Can you be a head-TA who is responsible for creating materials, coordinating among TAs, solving conflicts, etc. for some large class? Another obvious approach is to lead research projects, where you learn to delegate work and coordinate schedules. Or you could organize a reading group or workshop. Consider ways to go a bit beyond the obvious: can you initiate and organize a new talk series on a topic not currently offered by your department, but where you can identify a clear need for the department (to name an obvious example, maybe there’s a need among students to learn about non-academic careers but your department isn’t offering this right now)? Is there funding to be obtained for bringing in an external speaker? Can you coordinate this event with other departments that have sufficiently overlapping interests?

Is there a way to learn about administering budgets? Maybe this happens by working with a PI in a lab within your department who has external grants. Or maybe there’s a working papers operation in your department that students occasionally edit for. Or maybe it’s just co-organizing a large conference and seeing everything that goes into planning, budgeting, and executing on the plan. You can learn a whole lot from being active on an LSA committee or trying to organize a session at an LSA annual meeting, for example. You can be creative here, it’s less about the details of the event itself and more about the skills you want to learn.

Another alternative here is to seek out this expertise completely outside your department or university. Maybe there are other organizations or volunteer experiences that can be beneficial to you. Maybe it’s a committee in your field’s professional organization; maybe it’s a student-led initiative in your university such as student governance; maybe it’s through an organization related to a hobby. This is all fair game.

Get some comms and teaching experience

If communications and teaching is your jam, focus on honing those skills. Are there opportunities to take on more responsibilities within your department? That can be in developing teaching materials and teaching directly, but also in contributing to re-designing the curriculum and working with faculty in your department to overhaul the existing offering in some lacking cases if you can identify them. Maybe it’s volunteering outside your department and working with underprivileged populations. Maybe it’s creating a popular science presence on social media, writing blog posts, recording videos, or otherwise being creative about communicating your science to broad audiences. Maybe it’s about designing new kinds of materials to attract diverse talent into your field. Maybe it’s about contributing to AP courses or other materials for school students. (You’ll notice that some of these ideas are linguistics-specific, e.g. since linguistics doesn’t really have a presence in formal education before college and because it tends to have some diversity issues both on the student side and on the faculty side.) Again, there are diverse opportunities here depending on your interests.

Do a side project

Some of the best ways to (a) learn the skills I’ve described above and (b) showcase that you’ve learned them are to create a project based on those skills. This would be something you could add to your resume and host on a website to show potential hiring managers what you can do.

So what kind of side project should you do? It depends on what your focus is! (I hope this is clear by now!) Here are some ideas:

• Add an experimental component to a theoretical project. Create a design document that explains what you are testing, create your target and distractor items, write your guidelines. At the simplest end, you might simply create a substantial number of items to test the grammaticality judgments for some phenomenon of interest.
• Take all your elicited example sentences from your consultant work and turn them into a searchable corpus.
• Use well documented techniques to do simple field experiments, e.g. with story boards, to confirm or elicit new semantic judgments.
• Learn how to use Praat, do a simple perception study.
• Add a corpus study to your paper.
• Create a database of typological properties of phenomena you’ve been studying in different languages; create a labeling strategy and label your data. Publish this resource or host it on your website.
• Add a computational component to an existing project, for example training a simple model on the data you’ve collected.
• Seek a research collaboration with someone from another department or university who may have the kinds of skills who people you will probably work with are likely to have.
• Find yourself an internship over the summer or winter breaks.
• Write blog posts about how the new tools you’re learning about can or cannot be applied to the problems you are studying (and why).
• Create new teaching materials, or new materials for science communication to lay audiences, or new visualizations of data you’ve previously collected (depending on what skills you want to develop).

Start making job materials

As with everything else, what you need will depend on the jobs you seek. Most obviously, everyone will need to have a resume. You can start creating a master document to collect everything you might want to showcase, design your resume, and create some content. There’s more to say, but that would be a whole nother post which I’ll leave to another time.

Create and polish your LinkedIn profile. These days, LinkedIn is the most common site that recruiters use to find talent (i.e., you). When you’re ready to start searching you’ll want to add the ‘actively looking’ banner, but even before then, you should have a picture, header, short bio, and at least some basics (education, experience) filled in. Spend some time looking at profiles or people who have jobs you want to have and see how they present themselves. Feel free to steal their wording and customize it for yourself.

Polish your personal website, upload some work you’d like to showcase and link from your resume.

Collect ideas for situations you might talk about in behavioral interviews, which require you to tell stories about events from your past using the STAR method,⁶ and which benefit tremendously from some prep.

You may need a cover letter. Read about those and make a draft.

You may need to create a portfolio of your work, for example for design jobs. If relevant start reading about that and creating the relevant content.

Start keeping track of numbers

Even before you start making a resume and actively making materials for your job search, it will be useful to start paying attention to things you can quantify. Much more than CVs, resumes benefit from quantifying results. You’ll often be counting things that would never appear on your CV, but in the context of applying for jobs with a broad applicant pool, and where the hiring managers may often come from another field, numbers help frame skills and accomplishments in concrete ways. Some examples of things you can quantify:

• How many publications, presentations, invitations, interviews in popular media? How many citations? How much impact on others’ work through being taught by others or through others replicating, extending, or otherwise building on your work?
• If you run experimental studies: how many studies over how much time? How many participants? How many techniques, locations, tools, money paid, papers resulting, citations, followups, papers that use your results to do further work? How many hours/days/../years using a method?
• If you collected data through consultant work: how many consultants? How many languages? How many example sentences / entries in your database? How many resulting papers? How many other users of your data? How much funding? How many field trips over how much time?
• If you teach or TA: how many courses and how many students? Alternatively, how many hours? How many materials now used by others?
• If you organized a speaker series or lab meeting: how many regular participants? How many guests? What was the budget?

There are various other examples in the sample resume bullets in my transferable skills post. Check out the notes at the end of the post for examples of cases where I wish I had done a better job tracking the numbers.

Summary

I hope you’ve noticed the strong ‘it depends’ flavor of this post. What you actually choose to pursue largely depends on what skills you want to develop, so doing a bit of the thinking I recommend in learning about Alt-Ac opportunities (aka how to get started) is key.

In all, I try to take a skills-first approach here. What you actually do matters less than the skills you learn and how you eventually showcase them in a resume and interview. You can be very strategic when you choose a project to work on or skill to study: think about the bullet point you’d want to have in your resume (maybe even draft it if it helps) and work backwards to plan how to substantiate it.

Also keep in mind that a lot of things can be learned on the job; if you don’t have the time to do some of the more time consuming things I suggest here, don’t fret. You might take a two-pronged approach: start applying to some jobs immediately, and also scrutinize your profile and hone in on specific things to learn or add, especially if your initial search isn’t getting you the kind of attention you’d like (and you’re pretty sure it’s not just because your resume needs work or because you’re not aiming for the right kinds of titles).