1. Introductin: Why am I writing this?

A few months ago I decided that I’d had enough of academia and started looking for a non-academic job - my first grown-up job outside a university. I’d applied for several non-academic positions towards the end of my PhD without any success, but this time around I felt more confident in my prospects. As it turned out, five applications for interesting jobs across a range of areas led to four invitations to interview and two offers within a month (at which point I withdrew from the other interviews). Of these I accepted an offer to work as an Energy Market Analyst with Aurecon, a large engineering consulting firm. On the whole the experience was very pleasant.

Why was it that the dozens of applications I submitted in 2019 led to dozens of rejections, but a much smaller number led to multiple interviews and offers this time? Part of it must be that the conditions are currently favourable for job-hunters, with a skills shortage that I suspect means employers are unusually open to hiring smart people without direct experience (Inger Mewburn’s The Thesis Whisperer blog has a great post on this with good data from 2021). Perhaps more importantly, I was more prepared to take advantage of these conditions than I had been previously: I had a better sense of what I might apply for, a better sense of how to prepare those applications, and a much better sense of what I could offer employers to make myself attractive as a candidate.

This post is intended to share some of what I’ve learned with others in the same position of looking at non-academic job options after years as a PhD and/or ECR researcher. My experience has been in the physical sciences, but I suspect it’s probably applicable to other quantitative fields too.

2. Which positions can young research scientists realistically do?

It’s common to hear university types say that a science PhD teaches a lot of generally useful skills, and that doing one can lead to all sorts of exciting endeavours outside academia. I agree with the gist of this, but I’ve always found these statements frustratingly vague in their lack of actionable information: what, specifically, might those exciting endeavours look like and how could I find them? Searching a jobs board like Seek or LinkedIn for jobs that list a PhD as required or desirable is likely to bring up a list of academic postdocs and not much else. That doesn’t mean that there aren’t positions where high-level research skills are valued: it’s just that they tend to use different language to mean this, rather than listing degrees explicitly (see another post from The Thesis Whisperer on this topic).

Look at jobs with “analyst” in the title.

I haven’t met many self-described analysts in universities, but to employers an “analyst” seems to be someone who does some mix of the following:

Maintain a high-level overview of a field, know what the big questions are and who’s working on them, and follow developments as they emerge.
Identify specialist topics within that field that it would be valuable to know more about.
Gather and curate data relating to those specialist topica
Structure useful questions relating to that data, answer those questions, and develop new insights based on what the answers turn out to be
Synthesise those insights into analytical outputs/products that are valuable for non-specialists
Communicate those outputs to generalists in the field in a form they can understand, learn from, and use to improve decision-making.

These are the same intellectual steps involved in conceiving, developing, and publishing a high-impact reserach project. If you can tell a story of a research project you carried from start to finish without using impenetrable jargon like “magnetic resonance”, “enantioselective”, or “molecule” then you can probably sound like a plausible imitation of an analyst.

My sense is that junior roles are more likely to focus on the middle stages of the list above - the specialist technical work to generate specialist technical outputs. Higher-level work combines that specialist knowledge with an understanding of its context, identifying valuable problems to be solved and translating the solutions back into communication aimed at generalists. I think that an ability to combine specialist investigation with generalist subject-matter awareness is one of the more valuable selling points of a PhD in science. Even if the specialist skills you’ve developed are completely irrelevant to anyone outside your research niche, the fact that you were able to develop and apply them as part of a larger research context suggests you could do the same again elsewhere.

You don’t need much specialist “domain knowledge” at this point—that’s something you would develop in step 2 above. You will need to demonstrate interest, enthusiasm, and a high-level (broad but shallow) overview of the area you’re applying for. You’ll be asked open questions about the area in interviews: if you can’t say something specific and factually informed, you’ll be passed over. Think about why you want to work in the area, what the current challenges and opportunities are, and so on.

Depending on your coding experience (Python is fine), you might want to look at “data analyst” positions too. There are certainly lots around, but my sense is that there are also lots of people with relevant qualifications applying for those jobs. My suspicion is that this makes research types less competitive: high-level thinking and picking up new skills quickly is less valuable when plenty of others alrady have those skills.

How high to reasonably aim?

You’re trying to sell yourself as someone very smart and flexible, capable of independently learning new things quickly and thinking about them critically, but who doesn’t yet have subject matter experience in the field. In my limited experience I’ve had the most success aiming at mid-level positions. I think this is because mid-level/junior managerial positions are likely to value critical thinking, good communication of technical concepts, and an ability to work semi-autonomously within a team - all good scientist traits. Here in Australia in late 2022 that translates to a pay range of roughly $90-140k total compensation (including salary + superannuation) or an APS5-ish level in the public service. These are roughly comparable to a postdoc total compensation of $110-130k.

My suspicion is that independence and flexibility are less valuable traits for junior positions and and may well even be seen as negatives (is this person capable of listening to instruction and doing what they’re told?), while senior positions will expect direct experience in the subject matter along with personal networks that academics are unlikely to have.

Using LinkedIn to find relevant jobs

I don’t really use LinkedIn, but I fleshed out my profiled with portions copied/pasted from my CV (lots of keywords, lots of skills) and started browsing job postings once or twice a week. Whenever I saw anything that looked interesting and achievable, I saved it and clicked the “Apply” button (even if I wasn’t actually going to apply). I assume LinkedIn’s algorithms were tracking this because my suggested jobs got more relevant over times.

Found something that might be OK? Call the contact person (on a phone!) and have a chat

Your CV is probably very bad (mine was), but it’s not hard to make it better.

My skills were more desirable than I’d thought - but my CV was almost certainly much worse.

Get it down to one page, and remove all publications and presentations (leave major awards). Remove fluffy stuff listing skills or hobbies.

Optimise for keyword/keyphrase matching

Think in terms of keywords and keyphrases: your CV is most likely going to be screened by a computer based on keyword matches, so the main trick here is to include lots of phrases that might be what they’re after. Here’s the start of mine - spot the key phrases. “data analysis”, “data processing”, “model-building”, “communicating technical concepts”.

Cull irrelevant technical stuff—including publications

Spot what isn’t there: basically any discussion of the actual research I did. There’s no way the computer reading your CV will care, but if you get to an interview it’s possible the interviewer will want to know (or more likely: they’ll want to prompt you to speak on a technical topic they know nothing about and see if you’re able to say anything that makes sense.

Link to niche/technical stuff that you host elsewhere

You have a website, which is good, so I’d link pages that list your publications, presentations, research interests. None of that stuff is helpful on the CV, but if someone’s considering hiring you they may well want to read more - linking it on an external site (that you run! impressive!) keeps the info accessible and the CV uncluttered.

Have a clear and positive story of why you want this position

Be interested in the area

Learn to describe your skills generally (but have specific examples)

Expect to be asked why you’re leaving academia

You’ve spent 5-10 years working to become a research scientist and have now decided that it’s time to do something else. It’s almost guaranteed that someone will ask you to explain why.

Nobody wants to be a fallback plan. If you give the impression of wanting a job but not necessarily this job, that’s a problem. Similarly, it’s probably not helpful to answer this question with personal failure (“I’m leaving because I couldn’t get a grant/postdoc”) or bitterness (“I’m leaving because the whole system is rotten and needs to be burned to the ground”). I think it’s best to talk about the positive things you hope to gain from a non-academic position. As a bonus, you can use those positives to gently skewer negative stereotypes the interviewer might already have about academics (“I’m not one of those people - I’m leaving because of those people!”).

Here are some examples of things I’ve said:

“The subject of my research work is important, but my work has felt detached from society. I want to feel I’m making a more direct impact.”
“I’ve enjoyed being able to work independently on my own projects, but at times I’ve felt isolated. I’d like to work more closely with other people as a team.”
“I like to talk to other people about my work and share what I do, but it’s hard when you work on something so specialised.”
“Academic work is precarious with funding tied to external factors I have no control over. I want to be somewhere I can have more agency in my own success.”

None of those are overly negative or a whinge. Each highlights desirable personal attributes: “I want to make an impact”, “I want to work with a team”, “I value communication”. Most do so by contrasting those positives against negatives that people might associate with academics such as prickly individualism, pointless overspecialisation, and detachment from reality.

Develop skills and general interest

It’s very useful here to be interested and broadly aware of areas outside your own: if you’re looking at positions in energy and renewables then go follow lots of experts in the area on twitter, read relevant policy documents, and spend some time thinking about what’s going on.

Laying groundwork

From the start of my PhD I was aware that most PhD grads do not become academics. That didn’t dissuade me from wanting to do research science and I was optimistic that I would benefit from doing a PhD - and I did! But right from the start, I was thinking about how to keep my options open and about what I could learn within research science that would also be valued outside. Some of my preparations for a possible non-academic future included:

Developing new skills within research that could be useful in the private sector, e.g. learning to use Python/numpy/pandas/matplotlib for data analysis and visualisation in my PhD
Developing hobbies and interests that might be valued by employers: home servers and networking, basic understanding of websites and self-hosting, foreign policy and defence, open-source intelligence
Building visible portfolios of work to demonstrate those skills, e.g. GitHub and this website.
Talking to ECR/PhD colleagues that left academia and managed to find good jobs and learning how they did it
Talking to friends and family involved in corporate hiring settings and learning what they’d typically look

An anecdote from near the end of my PhD

Near the end of my PhD I was aware there probably wouldn’t be a job waiting for me at the end. I couldn’t yet tell if I’d be competitive for postdocs (I’d just started writing my thesis!) so I began looking into non-academic jobs. Unable to find any positions that would use my specialist chemistry skills and with little confidence that employers would value my PhD over any other tertiary graduate, I submitted applications for dozens of entry-level graduate programs in government and industry.

I received no interviews and no human feedback. The whole thing was grim and demotivating.

Finally, I submitted a single application for a mid-level public service (APS5) position with Defence (I’d become interested in defence issues during my PhD). I assumed I was hopelessly underqualified but to my surprise I had a call a few days later from someone willing to fly me down to Canberra, pay for a hotel, and put me through a round of interviews. I didn’t get the job, but the experience gave me a massive confidence boost after months of what felt like flinging carefully-written applications into the void. Talking to the hiring I learned:

At least some non-scientific employers saw value in my PhD skills and training, even if they didn’t care about supramolecular chemistry.
General skills in independent learning and project development were more valuable for a mid-level position (expected to work independently) than for entry-level position with less independence.
Applying for a more interesting senior position was a much nicer experience than applying for grad programs as one of thousands.

At the time I wasn’t able to test any of these thoughts - I had a thesis to finish, and had stopped applying for jobs. But I kept them in mind for later when I might find myself in the same position again.