Do you keep pushing forward in academia, betting on being one of the few to land the coveted tenure track? Or do you leap into something new and carve your path outside of academia?
Only you have the answers to those questions, but it’s okay to be uncertain about the future.
While we can’t tell you with absolute certainty what path is right for you, we can help you get started if you choose to transition out of academia.
We want to help you with your first draft of a career change by showing you what to expect at the beginning of the process. The four steps outlined in this blog are just the beginning. When you are ready, download the newest ebook, “Find Your Dream Data Career.”
Step1: Assess the Career Landscape
Academic jobs are highly competitive due to their scarcity. Multiple studies found there is less than a 50 percent chance of finding an academic job after completing a PhD program, and only about one in three jobs are on the tenure track.
As an applicant, you’ll spend most of your time in the job market completing applications, preparing your statements and personalizing those statements for each institution.
What’s the probability of getting a job versus the time that you’re investing in applying to them?
As a PhD candidate, you’re submerged into the academic environment. You’re working closely with your professors who were lucky enough to secure a tenure track position. Because of this, professors may incorrectly perceive the academic path as stable. This is a false sense of reality, which can be projected onto the students looking to their professors for advice and counsel.
Most importantly, the first step begins with knowing what you want out of a career. What matters to you? Assess opportunities based on factors like potential job satisfaction, location and work-life balance.
If you decide to move out of academia, the rest of the steps are a guide to help you on your path forward.
Step 2: Craft a Stand Out Resume
A quality resume is well organized. Based on feedback from our hiring partners, the ideal format includes technical skills first. Make sure the information is clear and concise. The first person reviewing your resume will likely be non-technical, making sure your expertise is easy to understand.
Next, highlight your work experience, which can be easier said than done when the bulk of your experience is in academia. The key is to stick with the most relevant work first, even if it is specific coursework or projects. It also helps if you have some examples of how you apply your technical skills throughout your career.
You want to make sure that your resume conveys your expertise and qualifications at first glance to every desk it comes across.
And while you want to include your academic experience, it might not be the most relevant.
Finally, customize your resume for each job application. Utilize the job description as a guide for how you list your skills and talk about your experience.
Pro tip: If you’re more familiar with the CV, it’s time to retire it because it’s too comprehensive for most companies and their hiring processes.
Here are some of our top resume tips:
- Be brief: A resume is a snapshot of your accomplishments and experience designed to capture interest. A resume is not a complete picture of what you can bring to a company (that’s why there are interviews). Eliminate any unnecessary information like jobs or skills that aren’t relevant to the job description.
- Avoid empty language: Words intended to create an impression but lack any concrete meaning. For example, “talented coder” is empty language. In contrast, “Contributed 2,000 lines to Apache Spark” can be verified on GitHub.
- Use metrics: “Achieved superior model performance” is empty language. Giving some specific metrics will help combat that. Consider “Reduced model error by 20%, and reduced training time by 50%.” Metrics are a powerful way of avoiding empty language.
- Carefully curate the personal information you plan to share: You can avoid bias in the hiring process by leaving off a specific address and instead just the city and state.
For a robust dive into how to build your resume and other essential steps in landing your first data job. Download our latest ebook, “Find Your Dream Data Career.”
Step 3: Show Off Your Projects
One of the more commonly used screening devices for data science is portfolio projects because they show the hiring manager that you have the skills necessary to do the job.
Not everyone who can write fantastic code knows what to do with it and why it matters. You’ve likely worked on projects in your career as an academic relevant to solving business problems, so talk about them.
A quality data project will include working with modern technologies, building models and showing how the data is making an impact.
Frequently, these projects are lacking context. Make it easy for the hiring manager to connect the dots. If you’re stumped and unable to see how your experience could apply in a business setting, then talk to someone in your network who might be keen on spotting the connections.
Step 4: Set Realistic Expectations for Your First Job
When you first start a new career journey, your dream job might not be your first job, and that’s okay. You may have several job titles and a couple of different companies on your way to the job that is just right.
Your concept of a dream job may even change after a few years of working in a new industry. So keep your options open and make sure you don’t turn down a job simply because it doesn’t check every box for you.
It’s important to keep your mind open and remind yourself of the following: You’re never going to regret taking the interview because it’s always great practice. So maybe the opportunity isn’t right, but at the least, you can practice interviewing in a low-risk setting.
When you complete a few interviews, you start to develop a flow. Not to mention, every job gives you valuable experience that you can add to your resume. And one important thing is that it’s easier to get a job when you already have one.
You’re no longer a newbie just looking for their first chance. You learn what you do and don’t like in a work environment, and every job is a step toward your dream job.
Many TDI students come into our programs, and they want to work at one of these places; Facebook, Apple, Netflix, Google or Twitter. Many alumni are working at those companies, but they didn’t start there, which was true for one Alumni, Newton Lee. He began at Crunchbase and then landed his dream job at Twitter.
Here’s Newton’s advice: “I think getting that first job is the hardest thing that you can do. I applied to dozens of companies for my first job, and most didn’t even respond to me. After working at Crunchbase for half a year, I started getting recruiters contacting me, cold calling asking me to work for their companies.”
You can hear more about Newton’s story in our Navigating Your Career Transition Out of Academia into Industry webinar!
So he landed at Twitter by getting his foot in the door somewhere else first. Remember, this is your first data science job. It’s not a lifelong commitment.
At TDI, we’ve developed an ebook that outlines the process from start to finish for landing your dream data job. Keep learning about how to transition out of academia by downloading your copy of the ebook.