For those seeking to move from academia to industry, one of your most important tasks will be to convert your CV to a resume. A crisp, brief PhD resume is critical when you apply for industry roles, serving as your starting point for conversations with a recruiter, hiring manager, or interviewer. It’s important to spend some time polishing your resume to capture your career journey, your strengths, and your research experience.
In this post, I’ll share 5 tips on how to polish your resume to move from a PhD to an industry role. These tips draw on my experience reviewing 100 resumes as an interviewer at Facebook and Google, empowering 50 PhD students to land jobs in industry as a coach, and having made the move from PhD to industry myself. My PhD research was with chimpanzees and I landed a role as a data scientist at Facebook via effective networking and a strong resume. I want to share these tips with you so that you can confidently make the leap from your PhD into an industry role. If you want even more details on how to make this leap, leverage my playbook, Academic Exit.
How to write an industry resume
Let’s start by setting out your goal and a key expectation as you begin to turn your CV into a resume:
Creating your resume is a process. You will start with a blank page, your CV, or some sort of resume template. You’ll need to identify key areas of your work that you want to highlight, prune those into pithy bullet points, and order sections according to the story you want to craft.
I’d recommend spending more time creating a solid 1-page resume than on any courses preparing new job skills. Learning how to convey your PhD research experience in a way that translates to industry will be one of the most difficult but important things to get right and it’s worth investing time in. My initial resume in moving from academia to industry took more than 10 iterations to produce something usable - but, now that I have that template, I’m able to edit it quickly for new roles. Putting in the upfront work to make a solid artifact matters.
Be ready to ask for help along the way. Prepare an initial draft of your resume and then run that draft by people whose feedback you trust. Early on, friends or colleagues can provide input on whether it is easily readable. Once you’re getting close to a polished draft, ask someone close to your target role to provide feedback on whether you’ve gotten the jargon right. If you don’t have a network connection in your target area, leverage “cold” applications and upload your resume to job sites to see whether it successfully passes through the screening algorithms.
If you have multiple target roles that you are applying for, you may want to create multiple versions of your resume. For example, if you are applying for both data science and quantitative UX roles, the focal areas of the listings may differ a bit. You may want to emphasize different bullet points or use slightly different phrasings. Where possible, list your skills using the same language as the description of the precise job that you’re applying for. If you’re uploading your resume to a job site, it may be scanned by an algorithm before it reaches a sourcer. This sourcer may not know the full details about the role and will have a certain set of skills they are scanning for. It’s important to make sure you’ve got the right keywords included and highly visible.
Your target is to create a resume that is quickly scannable, easily understandable, distinctive relative to other candidates, and straightforward in presenting the right keywords that demonstrate why you’re a great fit for your target role.
How to describe your PhD research experience and publications on your resume
Tip #1: Keep your industry resume short
For a CV, length is helpful. As a graduate student, I remember hearing praise for my CV being “as long as my arm.” For an industry resume, in contrast, shorter is better. Everyone in industry is busy, tasked with way more work than they have time for. You may have only seconds to make an impression on a recruiter, hiring manager, or interviewer who is scanning your resume. It’s critical therefore, to edit your resume down to the essentials to get your message across quickly. I’d recommend 2 pages max. 1 page is even better.
Keeping your industry resume short may be difficult, so it’s OK to start with something longer and prune as you edit. Focus on getting the content first and then whittling down to the points that matter most.
Tip #2: Clearly convey your relevant industry skills
Unlike a CV, where selling your topic matters, for a resume, your research topic is less relevant for an industry role than the skills you bring to the table. Unless you happen to be applying to a job where your area of graduate expertise is relevant, what’s more important is how you got work done in grad school rather than what you’ve done.
You may be saying to yourself, "but wait - I don't have any relevant skills!" You do. You just need to figure out the language with which you can convey those skills so that they come across as relevant in industry.
If you’ve been conducting informational interviews (get my free guide here), you’ve started to pick up on some of the buzzwords of the fields you’re interested in - data analysis, project management, user research, experimentation, statistics, etc. You can also learn these buzzwords from listening to people speak about their experience (like they do in my Career Explorer series).
Your goal in creating your resume is to translate projects that you’ve done into bullets using that jargon. Ideally, your bullet points should be easy to scan even for someone with little to no expertise in your academic field.
In addition to your informational interviews, you can pick up relevant jargon via job descriptions. These often provide great examples of the types of verbs and nouns that the job is looking for: led, analyzed, defined, collaborated. Think about what you’ve done in grad school using that same language. Did you take in fMRI data, clean it using Python and leverage R to analyze the outputs? Mention your skills in analyzing unstructured data. Did you lead a team of researchers to carry out a multi-year series of experiments? Mention your skills in team leadership and project management. Begin to shape your PhD research experience into your own personal story of experiences so that you can clearly articulate what you can (and can’t) do.
Tip #3: Quantify the outcomes of your academic research for industry roles
Successful resumes spell out concrete, numerical outcomes for the work that the candidate has done. Concrete outcomes make it easy for the reader to understand the “deliverables” or outputs that your work has created.
This is particularly important in areas of academic work that are niche-specific. The person reading your resume may have no idea why the bend in that specific protein you sequenced was relevant. Make it abundantly clear what you did and what impact that had: “Sequenced 25 proteins to identify a candidate for an HIV treatment.” Quantities make it easy to understand the outcomes across any field.
Early on in shifting my own CV to a resume, I remember really struggling on what to quantify. So I started off by quantifying what I was most proud of - the thousands of saliva samples I’d collected for my studies of ape behavioral endocrinology. The latter half of that sentence didn’t matter much in the Tech industry - behavioral endocrinology isn’t a big deal to Facebook (yet). In retrospect, even the fact that I’d collected two thousand samples was a speck’s worth of data relative to the scale of the data that I would eventually work with at Facebook. But, unwittingly, by quantifying those saliva samples I was able to call out that I’d analyzed that data in R, which happened to be relevant for data science positions since it showed that I was able to script. My work with that data set made it clear that I could work with datasets larger than those that can fit in an Excel spreadsheet, which was critical for a data science role.
My recommendation, then, is to start off by taking what you’re proud of and what you can quantify. Here are a few questions to spark ideas:
Start with what you are proud of, re-read and get input from others, then revise, cut, and repeat.
Tip #4: Be sure to include a strong summary statement for your resume
The beginning of your resume is your chance to capture your career journey in a few short sentences to tell the reader who you are in a few short sentences. In my opinion, summary statements help because they put you in a straightforward bucket that is easy to remember. If a recruiter is looking at 25 resumes for a data science role and only one of them comes from a geneticist, that enables you to stand out.
Coming from academia, it may be hard to figure out your own bucketing at first. This is a place to experiment and iterate. For inspiration, check out profiles on LinkedIn that have a solid one-sentence summary. Tailor your summary statement using words from the job that you’re applying for. Say you’re a geneticist applying for both roles in BioTech as well as roles in Data Science. For the former, your resume may have a summary statement like: “I am a geneticist with 8 years of experience in bench work, including CRISPR.” For the latter, your summary statement may instead highlight: “I am a quantitative geneticist seeking roles that leverage my experience with unstructured data sets.”
You get to pick the topics and language to highlight your strengths and journey in the summary statement for your resume. As much as I dislike labeling or putting people into buckets in general, a resume is a good place to do so.
Tip #5: Leave no major gaps on your industry resume
As an interviewer at Facebook and Google, I would quickly skim a candidate’s resume so that I could walk into an interview knowing what skills I needed to assess. I would look for gaps between the role I was interviewing for and what appeared on the resume. If I were interviewing a linguist for a data science role and his resume didn’t mention any statistical techniques, I would focus on questions assessing his knowledge of probability. If I were interviewing a physics PhD who hadn’t put any examples of collaborative work on her resume, I would ask her a behavioral question to get a sense for how she would work in teams.
My recommendation for you, therefore, is to do your best to address each of the major categories of skills with bullet points on your resume so that there are no “obvious” gaps. That’s not to say that you need a bullet addressing every requirement from the job listing - you very much do not. For each bucket of skills (quantitative, bench, leadership, etc), creating a bullet point that demonstrates your capacities will create fewer perceived gaps.
You can move into an industry role with a PhD in a "niche" discipline. After all, my PhD research was with chimpanzees! Learn more about my experience on my About page. I had a client say to me once, "if someone can land an industry role with your research experience, anyone can!" And she was right. You can make this transition too. But, you will need to polish your PhD resume in order to move into industry. You will need to use your resume to confidently, concisely, and clearly convey your skills. Once your resume is ready, you will find doors open to you that you might never have imagined.
I'll be sharing these tips and more in a free webinar on How to Build a Kick@$$ resume in the first week of October. Join us and bring your resume for feedback!
As you embark on your PhD job search, you may be concerned about your qualifications — particularly if you are considering a non-academic path. My PhD clients often ask:
Here's the good news: as a PhD-holder, you are already qualified for a number of existing roles.
Your task is to find a job that is a good fit for you — not to contort yourself into some mask of generalized marketability. By taking a fit-based approach, you shift from a mindset of worry ("am I skilled enough?") to one of fact-finding ("where can my skills be most of service?")
If you are considering a non-academic path, you are not alone. Fewer than 50% of PhDs now finish their doctorate with a job offer in hand. That percentage is declining decade over decade. Nearly 50% of PhDs in the US will end up taking a job in industry. Yet 60% need to seek career guidance online because they don’t get adequate mentorship within their institutional environment.
In advising more than 50 PhDs on their career paths, I have uncovered a number of techniques that enable folks to successfully land non-academic jobs. Below I have listed 4 such strategies.
Strategy 1: Stop Reading Job Ads — For Now
This sounds impossible, right? How can you learn about jobs without reading ads? Won't job ads give you an idea of the skills you need in order to be worthy of a job?
The problem with job ads is that they are like a Tinder profile with airbrushed photos: they represent a distorted view of what a role will be like in reality. Moreover, they may spark insecurities about your own qualifications. Notice the "worthy" terminology that I used above? Ever found that you feel unbelievably unworthy after perusing job ads (or looking at hotties on Tinder, for that matter)? Reading ads can put you in a low-power and low-self-esteem mindset. This is not where you want to be as you embark on a job search.
Instead, I recommend exploring roles using a tool called informational interviewing which I will describe in more detail below.
You can start reading job ads when you begin to apply for jobs, since these ads contain buzzwords for your resume. But that brings us to another strategy that may seem counter-intuitive…
Strategy 2: Do Not Apply To Jobs While You Explore
Too often, I see job-seekers start sending out applications left and right without any focus or decision-making upfront. This approach allows them to get some feedback if they luck into landing interviews. But, it often yields a whole lot of rejection. And this rejection can make them want to give up on their job search entirely.
To counteract rejection fatigue, I recommend that you take at least 3-4 weeks to explore roles before you submit any job applications. Using the information that you gather in info interviews, you can make a decision on 1-2 target roles. With target roles in mind, you can tailor your resume towards those roles, thereby increasing your chances of success. By sending out only focused applications, you will encounter less rejection throughout the job search process.
Strategy 3: Start Conducting Informational Interviews
So by this point you may be wondering - what are these informational interviews that Tory keeps mentioning?
An informational interview is a 30 - 45 minute conversation where you ask someone for information about their job. These conversations allow you to assess fit with a given role, company, and industry. Unlike a date with the airbrushed Tinder hottie, an informational interview is like a date where you have been set up by a friend.
From conducting informational interviews, you can uncover:
And those are just the role-specific areas that you can learn about — not to mention the information that you can gather on an industry, company, or a specific team. Can you tell how much I love informational interviews?! If you are curious to learn more about how to leverage informational interviews in your job search, I have a free guide available here.
Strategy 4: Learn the Local Language
By definition, jargon varies dramatically across industries. To move from academics into an industry role, you're going to have to learn a new set of terms and new way of speaking about your work.
Fortunately, you can uncover the language of your target industry during informational interviews. The phrases you hear repeated over and over? Those are your buzzwords. The language that your interviewees use to talk about their background? Borrow the elements that work for you. By learning these targeted ways of speaking about your experience, you will increase your credibility as an "insider." This practice is similar to traveling to a new country and learning a few phrases beforehand for how to navigate — these phrases go a long way in communicating with the locals.
To illustrate this strategy, let's take a detour into my own experience in moving from academia to industry. As a science PhD, I had done quite a bit of statistical analysis in my doctoral research. But, I had no idea that this was a marketable skill until I started conducting informational interviews with data scientists. Soon, I recognized that terms like unstructured data, A/B testing, and multivariate statistics mattered to folks working in this field. By identifying ways to incorporate jargon terms into my own career narrative, I was able to bridge the gap. Doing so mitigated risks that might have come to mind in offering a job to a chimpanzee researcher — instead, they could feel more solid in offering a job to a scientist experienced in statistics and A/B testing.
Importantly, in learning the local language, you are not learning any new skills — you are just learning a new way to describe skills you already have.
Conclusion: Your Mindset Matters
As you start using these strategies to find jobs, you may still run up against self-doubt — moments where you wonder whether you are qualified for anything. In those moments, remember that you are on a fit-finding journey and not a journey where you need a job in order to prove your self-worth.
The job that aligns with your goals and strengths is out there now, just waiting for you to find it.
Curious for more tips on your PhD job search? I've distilled what I have learned from coaching more than 50 PhDs into industry in Academic Exit: a playbook for you to move from academia into industry without studying.
I'm writing this blog to share my perspective on career transitions, time management, and personal growth.