Aditya Sharma 7m 986
The views of this article are the perspective of the author and may not be reflective of Confessions of the Professions.
Data science jobs are taking over the world, literally!
With a projected growth of 27.9% by 2026, which is much higher than most industries, companies have observed the need for data scientists. Statistics from Analytics Insight predict over 3M data science job openings in 2021 alone, and that number will only grow hereon.
Like other jobs, increased demand in the job market means that more people will go into the field by attending training and receiving relevant certifications, like you. So, there are thousands of applicants for a single job.
Such a saturated job market means that you need to create a killer first impression, and in the world of job hunting, that would be your resume. In this case, what you have to do is elevate your data science resume to stand out from the rest.
Here are 5 steps you can follow to get yourself a job-winning resume!
Contrary to what you might have known all along, you should not be sending the same resume to all of your jobs. Recruiters of high-profile companies want to see a personalized resume that fits their expectations perfectly.
To create a master data science resume, you need to put all of your information in one place. All of your certifications, training, research projects, and work experience will go here in organized sections.
Then start to cherry-pick information that you think will be relevant to a particular role. The ideal way to do this is by cross-referencing your resume and the company’s job description. Take a look at the requirements section to figure out what you must add to your resume.
Tailoring your resume will make it easier for your recruiters to make a judgment on your suitability for the job because your data science resume will only have relevant information.
Used by companies, the Applicant Tracking System (ATS) is a software that makes the recruitment process easy. It weeds out resumes that do not meet the job description, so you need to make sure that you tailor your resume to the company’s needs.
Job descriptions play a bigger role than just give you an idea of what your job would entail, it holds the key to the job itself.
Scan the roles and responsibilities section of the company’s job description and hunt for any recurrent keywords or important functions. While you are at it, scan the requirements section as well, and note down what you think the company wants.
While you draft your resume, try to include those keywords that they enlisted in the job description. Believe it or not, the ATS will screen your resume based on those keywords.
Now hold on, this is not your license to bombard your resume with repetitive keywords. If you pass the ATS, your resume will land to a human recruiter, who will spot your spammy resume in less than a second. If you do not want to land in the reject pile, be sneaky with your keywords.
The ATS checks if you’re familiar with industry standards and if your data science resume is legitimate. So, if you planned to use a double-column resume with an inconsistent format, scratch that.
Choose the reverse chronological resume format as it adds to your credibility, shows your entire career trajectory in a simplified manner, and is the industry standard. Use a single-column resume template and make sure that your fonts are consistent throughout.
Refrain from drafting paragraphs upon paragraphs of all the functions that you performed at your previous jobs. Optimize it by following these tips:
- Provide your work experience in one-liners as a bulleted list and start them with power verbs
- Maintain a cause-effect relationship in your sentences to give a fairer idea of the functions you performed
- Highlight important points and gather similar functions under relevant subheadings
- Quantify your work experience wherever possible to give a solid figure for your hiring managers
Your entire career trajectory must be readable at a glance, so make them as concise and information-packed as possible!
With the 7.4 seconds that your recruiters have to assess your expertise, you need to serve your data science skills on a platter.
Split your skills into key skills for all the hard skills you possess as an employee, and technical skills for all the tools such as programming languages and software that you are familiar with.
List them in condensed form next to each other, and this will give your hiring manager a well-rounded idea of your areas of expertise at a glance.
In addition to all the usual resume sections, you can customize your data science resume to add any extra sections that you think are required for your unique career trajectory.
You can add sections like certifications, training, projects, research interests, etc., based on how relevant it is to the job you are applying for.
Creating a stellar data science resume is really not rocket science, and you can crack it with the right guidance. Here is what you can take away from this article:
- Create a master resume with all of your information in it and choose what to add to your resume for each job by assessing the company’s job description
- Follow industry standards to ensure that your resume is ATS-compliant by making sure that you are using relevant keywords and the right resume format
- Give your professional experience section a facelift by splitting them into bulleted lists with one-liners and maintaining a cause-effect methodology
- Capitalize on all of your data scientist skills by making separate sections for key skills and technical skills
- Add any extra sections that will compliment your career trajectory as well as the job requirements
Now, ace your job hunting process, and we are rooting for you to finally bag that job!