Interview Process

Many people think that they'll start applying for jobs when they become proficient in things that are required in the market, and becoming proficient will take time, so they end up not applying for jobs. This is not true for data science because the demand for data scientists is rising, so you won't lose opportunities even if you don't get hired.

Try to make your portfolio and then start applying. This will expose you to what you can expect in data science interviews. Every experience counts and will make you a stronger candidate for the job.

Profile screening

The first thing data science recruiters do is screen your profile. This is a multistage screening process that includes application screening, resume screening, cover letter screening, social profile screening, and portfolio screening. Let's learn about each of these stages one by one:

• Application screening: You will apply for jobs through a web portal, and they will check whether you have filled all the required fields appropriately or not.

• Resume screening: They check whether your resume is up to date and if it matches your social profiles like LinkedIn.

• Cover letter screening: They will check if you took time to write the cover letter or copy-paste the stuff in the resume or from the internet.

• Social profile screening: They will check if your experience, skills, and expertise mentioned in your social profiles match the details in the application and resume.

• Portfolio screening: As a data science enthusiast, you must have a portfolio of projects, and they will indeed check your portfolio to understand your competency level by analyzing your projects.

All of these screenings are done in steps. If your profile passes the application screening stage, then it moves to the resume screening step, and so on. Therefore, it is necessary to carefully design everything you need or want to showcase to prospective employers.