How can we prepare for data science interview?

22-Apr-2021

The right interview can lead you towards that professional role for which you have planned until now - to grab a seat at! 

Right portfolio/CV pitched to the Right employer at the Right time - this is all you need!

Taking up Data Science certification, enrolling into the right Data Science course, and then landing up at the interview, is what should be normally done to sit at the right Data Science role that the professional IT and business world offers you.

These are - Data Analysts, Data Engineers, ML/AI Engineers, Data Scientists, and other related roles. Majorly, the job roles of Data Scientists and ML/AI Engineers are grabbing more importance in the modern 21st century, currently. People are hit by Covid-19, they have lost jobs.

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In these uncertain times, they are relentlessly searching and applying for other jobs. So, in this unwanted and changing scenario, people must ensure what they are capable of in reality, and how they are appearing before the employers who will ultimately judge them sitting on a higher seat. Mainly, the two appearances must coincide.

If they have skills, potential, and capabilities then, these must duly find and reach the potential employers and companies that are hiring for skillful and expert employees. 

Some of the necessary steps that must be assuredly taken into account by the aspirants who are looking forward to career opportunities in Data Science -

• Getting an authorized certification/program from a reputed institution or university can open real gateways!

Getting a valid certificate or degree in Data Science is mandatory to get that dream job. While you sit as an interviewee and the employer takes your interview, you must have a good certification that speaks honors and laurels for you.

A good certification that has a worldwide authorization can help you impress the employer in a flick of time!

• Picking up the right course!

Moving forward, the candidate must know what s/he is picking for herself/himself. The course must be selected following the post s/he is going to target and sit for in the future.

Different courses upgrade students in different skills, technicalities, lessons, and aptitudes. Here, the learners need to choose wisely! Select the course that fills you with the needed knowledge and not any extra irrelevant knowledge that is beyond your discipline. 

• Mapping the Skill-set!

When you target and prepare for the job posts of Data Analyst, Data Engineer, Data Scientist, and AI/ML Engineer, you need to cover different Data Science topics.

For instance, for a Data Analyst, the learner must work on Data Cleaning/Wrangling, fundamentals of Statistics, SQL, Python, Google Analytics, Tableau, and in many varying cases, as demanded by the organization, on Excel.

If you are targeting Data Engineer then, Competent Programming/Development skills, REST APIs, etc, Big Data tools — spark, Hadoop, airflow(DevOps), knowledge of web frameworks, developing ETL pipelines, and development of Cloud Service Providers is a must. 

Therefore, it is very important to show all these skills in your CV while you go for the interview. Also, looking at the JD and analyzing what the employer needs can also help learners and aspirants in preparing for the Data Science interview. 

• Preparing the candidature/portfolio or the Curriculum Vitae.

After noting what all is needed, the aspirant can bring in all the needed and necessary skillsets and pin them all up in the CV/portfolio.

Besides, the aspirant can note how s/he can make the CV attractive and the interview more profitable that opens up possibilities for his/her hiring by the organization. 

• Sitting for the Interview. 

This is the last stage. After the candidature is complete and the aspirant knows what s/he is supposed to do, the learner is ready to sit for the interview.

The learner must note that s/he has read the job description and he has all the suited Data Science certifications and degrees to make it big in his interview and career alike!

Major Topics that Need Preparation - 

●  Good programming expertise in Python, R, and Matlab.
● A profound comprehension of Mathematical and Statistical concepts.
● Classification and Regression problems.
● Supervised and Unsupervised learning.
● Natural Language Processing.
● Experience in Data Science libraries such as Tensor Flow and PyTorch.
● Cognizance of many Data Engineering tools.  

Helpful Links

Data Science Algorithms – Aspirants Must Know

Why Python Language is the Best Choice for Data Scientists?

What is the Current Demand for Data Scientists?

Is Data Science Really a Rising Career?

How Long It Will Take to Learn Data Science?

5 Things Every Aspiring Data Scientists Should Do

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