3 Things That Look as Good as Experience on a Data Science Resume
So you need a job in data science, but you don’t have company experience. It’s a Catch-22. You have to get hired to get experience, but you can’t get hired without the experience. Getting over that hurdle means getting a little creative and applying other factors to your data science resume (truthfully, of course).
[Related Article: 3 Unique Ways to Get a Job in Data Science]
The great news is that data science is changing the way companies hire. The traditional “must have five years of experience and blah blah blah” is going out the window in favor of “must-have results.” That means you can showcase your talent and accomplishments right into a great position.
Showcase Your Projects
You did some cool things in school, right? You need to add these to your data science resume. Instead of just listing what you did, however, keep this particular spin in mind. You’re solving business problems for a company with your data science expertise.
Your projects may not be specifically business-related, but think about how you could apply what you did to a business perspective. Businesses are interested in data science for the business value it creates, not the coolest new algorithms you’ve written. Think about why a company might be interested in a specific project you did.
Projects from this perspective showcase what you’ve already accomplished and how it could be applied to the company. It’s a bit like showcasing a house. You stage the house so that the new owner could see themselves living in it. With your resume, stage it so the business can see the way your projects benefit the company.
So how do you do that? Set it up in scannable bullet points.
Name of the Project
- A quick explanation of the purpose of your project. Be brief. No seriously, brief.
- A couple of sentences about how you built it.
- The tools you used
- A sentence about how the same principle might apply in business
- Link to the project
And that’s it. Hiring managers are skimming resumes, so you want to get to the point. Save the details for your interview.
Showcase Your Hackathons
Hackathons are great for gaining experience and showing businesses you have creativity and initiative. Hackathons are responsible for innovative projects like Facebook’s messaging capabilities, and where would you be without that now?
These hackathons can go in the “projects section” of your resume, or if you’ve had one or two standouts, in their own section. The advice remains the same, however. Only include hackathons that you can spin for business value and avoid a long string of random hackathons with nothing to tie them together. List them similar to projects if you choose a different section for hackathons and remain brief.
Your ideal company may already be hosting hackathons, and if that’s the case, you have even more reason to get involved and showcase the results. Hackathons for companies within the same field and possibly competitors as well could trigger interest. No one wants to lose talent to one of their top competitors.
Volunteer Work Counts
Volunteer work is an excellent way to gain experience and do some good in the world. Data science can be done remotely, so you aren’t even tied to your general area. Find a cause you believe in and get to work.
When you identify a potential volunteer opportunity, reach out, and offer your services. Let them know how you might be able to help and what benefits they could expect from working with you.
Volunteer spaces aren’t there for your personal development, however. Be careful not to go into it only with the intention of using it as a resume piece. If you can find a cause you believe in and an organization you support, building that volunteer relationship could help flesh out your resume as a side benefit.
To find volunteer positions, look on www.idealist.org or www.catchafire.org to help match your skill to organizations in need. Also, research what’s in your local area if you’d prefer something local.
Finding Your Stride in the Data Science Job Search
Traditional hiring strategies are on their way out in favor of dynamic hiring that considers results and not just time-based experience. However, many HR teams are still coming from a traditional perspective. Getting your resume in front of the right people means designing it to highlight what you bring to the table specifically for that organization.
[Related Article: Making Sense of Confusing Data Science Job Postings]
The best piece of advice is to tailor each data science resume to each job. It takes more time, but you’ll see better results from this approach. Demand in the field will only get you so far. Use your resume as a tailored showcase of what you can do for that specific company can help take you the rest of the way.
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