What skills should be listed down on Resume for Data Science Jobs?

Data Science, AI and ML
#1

There is an endless number of skills that you can mention in your resume but the question is – should you cramp 10 of your unproven skills or 3-4 strong hands-on skills? The answer is, as you might have guessed, the latter. The interviewer will be expecting you to be good with each skill you have mentioned.

Let us take up a few points one-by-one and discuss them:

  • Prioritize skills according to the job role
    The interviewer has a very specific demand for hiring any personnel. You have got to mold your resume according to the job description. For example, the job description requires a candidate with a strong Python and machine learning stronghold. Whereas you have a stronghold over Python, machine learning, and deep learning. To show off, you include all the projects related to deep learning and miss out on machine learning projects and skills. This might set off the recruiter and you will lose your chance to a coveted job.
  • Mention data science projects
    As I mentioned in the above questions, practical knowledge counts more than theoretical knowledge and data science projects are a clear way to showcase your skills. Try to mention projects which will showcase each of the skill you have included.

  • Don’t forget your GitHub profile

Nowadays, a GitHub profile is a must if you want to go for a data science job unless the required skills are only Excel or SQL. A Github profile instills confidence, trust, and flexibility to check out any project that you have mentioned in a resume. It is a sure shot way to win the heart of the recruiter.

  • The overall resume counts

No matter how capable you are unless the resume gives a clear picture of you or your skills, you won’t go to the next stage. Therefore, be precise in the format, font, structure of your resume. You can check out the below video posted by Google. It has some amazing guidelines and recommendations for building a great resume.