Non-traditional ways to bag data science job roles in 2022

In 2022, the job aspirant, along with possessing the right skills, has to push their boundaries to set themselves apart from the crowd, to bag their dream roles

A job role as a data scientist is a dream for many. But in 2022, the traditional ways of getting into analytics is just not enough. Even after your concepts are crystal clear, an aspiring data scientist cannot expect to land their desired jobs just by applying when they see job openings. Times have changed, and one has to take other proactive steps to ensure that they crack the interviews that will land them in such rewarding roles.

Here are a few ways to ease the process of landing data science job roles this year.

Hackathons and competitions

Hackathons and competitions are a great way to test one’s own skills and understand what is needed out of you as a data scientist. Kaggle has emerged as a go-to platform for aspiring data scientists as well as those who are already in the profession to prove their skills and compete with like-minded people.  MachineHack is another immensely popular platform that frequently hosts challenges and hackathons to solve problems through data science and analytics.

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Active participation in different hackathons is a great way to learn new skills as well.

Ayan Basak, who works as a data scientist at Snapdeal, says, “According to me, hackathons and competitions are very important components of one’s portfolio for a data scientist role. Especially for me, coming from an electronics engineering background having no formal education in DS, it has been a huge factor to advertise myself. It has also helped me to develop my technical knowledge and navigate across various challenges one might face in this domain.”

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Start a podcast, YouTube channel

As the world keeps consuming more and more visual content, starting a YouTube channel talking about data science and its various components can be a great way to boost one’s resume. Podcasts are ever so popular now. It is the right time to start a podcast talking about data science, AI and the whole analytics landscape. Of course, this works mostly for experienced people who have already spent some time in the field.

Venkat Raman, co-founder, Aryma Labs, adds, “The candidate must ensure their content stands out. Run of the mill content, which everybody is doing, will not help. One suggestion I can give is, perhaps, candidates can review research papers, unpack the complexities and explain them in simpler terms to the general audience. Companies are always appreciative of people who are great explainers. As a data scientist, explaining things well to various stakeholders is a key skill.”

Share work through blogs and demos

Some concepts in analytics can be very complex. To a potential recruiter, a candidate can also get noticed if they can explain their previous work in simple words through blogs and demo videos. Maintaining a blog can be an effective way to get noticed by recruiters. 

Raman, who frequently recruits data scientists, says, “As a data scientist recruiter, I am constantly on the lookout for candidates who share their ideas or work via blogs and demos. A candidate could stand out of the crowd if they can explain a complex data science concept in simple words. Similarly, a demo of innovative application of data science techniques to a problem could help the candidate get noticed by top firms.”

Conferences and meetups

Conferences can be a great place to network with recruiters, senior professionals and peers. If you find your desired company participating in a conference or holding a meetup in your city, you must attend as it will give you the opportunity to meet the people working in that company and understand what skills are needed to land a job there.

Showcase your work on GitHub and similar platforms

Showcasing your work on GitHub can act as an online resume for data scientists and machine learning professionals. A hiring manager can look into your GitHub profile to see what kind of work and projects you have done. Nowadays, it is almost mandatory for data science aspirants to have a GitHub account to create a repository of your work. Basak adds, “It helps showcase one’s technical as well as presentation skills. It also helps the interviewer gauge the kind of work you have done and whether you are fit for the role.”

In 2022, the job aspirant, along with possessing the right skills, has to push their boundaries to set themselves apart from the crowd, to bag their dream roles.

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by Vijayalakshmi Anandan

The Deep Learning Curve is a technology-based podcast hosted by Vijayalakshmi Anandan - Video Presenter and Podcaster at Analytics India Magazine. This podcast is the narrator's journey of curiosity and discovery in the world of technology.

Sreejani Bhattacharyya
I am a technology journalist at AIM. What gets me excited is deep-diving into new-age technologies and analysing how they impact us for the greater good. Reach me at

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