3 Tips for Getting a Job in the Data Science Field
The internet has not only created myriad new jobs but also invigorated fields like data science, which combines math, statistics, analytics, programming, AI, and various tools to analyze large amounts of data in order to extract information and insights that help businesses grow and improve. Data science is vital in the modern-day business landscape, with those who take advantage of its power shooting ahead of the competition.
Lots of people aspire to a career in the data science field, whether they’re just graduating from high school, completing a university degree, or looking for a change in profession. This means there is intense competition even for entry-level jobs, but don’t let that discourage you! Facing stiff competition is not that big of a deal if you’re better qualified than most other applicants, so work on making yourself the best candidate you can be.
If you’re keen to work in data science, you need to approach the job application process the same way you would in any other field: Do your research, learn what the role you want requires, and understand how your skills and experience qualify you for it. First, you need to identify what type of job you want as well as your longer-term career goals in the field. Look for jobs that set you on the path you want to follow, and if you don’t yet have the necessary skills or qualifications, consider how you can acquire them.
Use your connections to network and get job leads, build relationships with industry experts, attend conferences and meetups, and showcase your work whenever you get the chance. Finding a job in any field is all about putting yourself out there and highlighting your skills, and it’s important not to lose faith in your abilities or the process, even if you don’t see results as soon as you expect. It’s rarely an easy journey, but ultimately, it’s always worth it. If necessary, get a freelance gig or a temporary job to keep you afloat as you pursue your data science job.
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So, what can you do to improve your chances of getting a job in data science?
1. Customize your resume for data science jobs
You should always tailor your resume to the position you’re applying for—employers want workers who truly care about the job and won’t up and leave when a better opportunity comes along, so generic resumes won’t get you far. Take special care when customizing your resume if you’ve been working in or applying for jobs in a field other than data science. To succeed in your job search, it’s imperative for your resume to match the skills required for the role you’re after, highlighting the qualifications and experience that make you an ideal candidate for this particular position. You want the hiring manager to be able to tell right away that you have the necessary qualifications—otherwise, they may just toss your application aside.
However, there’s another reason why tailoring your resume to each position is extremely important, and that’s the applicant tracking systems (ATSs) most modern-day companies use. These computer programs filter out candidates they deem irrelevant, which means that failing to customize your resume for a given role puts you at risk of having your application thrown out before a human even sees it. Scan the job posting for keywords and include as many as possible in your resume, but make sure you’re being truthful about your skills.
Remember that not only is it important for your resume to be well-written and honest, but it should also be concise and visually appealing. Try not to go over two pages, and if you’re just starting your professional journey, keep it to a single page. Hiring managers often won’t even look at resumes longer than two pages—they just assume you either lack communication skills or are showing off.
You want your resume to stand out for all the right reasons and present you as the best person for the job, so give it the time it deserves if you want it to do the heavy lifting for you. It’s a short document, but each word you put on the page carries a ton of weight. If you’re not sure where to start, let our experts write or overhaul your resume to optimize it for hiring managers and ATSs.
2. Learn new skills and get more experience
If you’ve been steadily applying for data science jobs but haven’t heard back from any company, you may need to take a step back and analyze your strategy. Perhaps you need more experience to put on your resume so you can qualify for the positions you want. Given the huge number of candidates vying for data science jobs, a rejection doesn’t necessarily mean you did anything wrong—it may simply mean the employer felt someone else was better suited for the position.
However, if you’ve been experiencing a string of rejections, that could indicate there’s something more you could be doing, so take the time to reflect on what may be holding you back. Don’t let rejection discourage you—instead, let it strengthen your resolve to improve your qualifications and become an even stronger candidate.
Competition for data science jobs is fierce, and you need to be able to back up your skills, so anything you can do to boost your profile will serve you well. Whether you work on improving your technical or soft skills, make sure you’re building on transferable, in-demand skills and taking opportunities to get more real-world experience under your belt, including internships and freelance work. What exactly you should do will depend on your individual circumstances, but as long as you’re earnestly working on your skills, you can’t go wrong.
3. Apply for your dream data science job even if you don’t meet all the criteria
While you work on enhancing your resume, gaining more experience, and building your personal brand, you should keep applying for all the science data jobs you’re interested in. Continue sending in those applications, write or get help writing a cover letter that you can tailor for each position, and keep scouring job boards for that perfect opportunity. You may not feel ready, but each opportunity is unique, and you don’t lose anything by taking your chances with an application (as long as you don’t let rejection bother you too much).
Even if you don’t meet all the criteria, go ahead and apply for that incredible job—you might be just what the employer is looking for. Don’t take it personally if you don’t get invited for an interview or if an interview doesn’t lead to a job offer—just keep going until the right vacancy opens up at the right time. Yes, it’s frustrating, but every rejection gets you closer to your dream data science job, so keep honing your skills, perfecting your portfolio, and tailoring your resume.
If you need assistance at any stage of your data science job search, check out our professional job services, which include personalized career coaching, mock job interviews, resume overhauling, and lots more!