Tips to Create a Data Science Portfolio and get hired as Data Scientist

Category: Data Science Posted:Aug 21, 2020 By: Ashley Morrison


How to become a data scientist? A question that pops up in the mind of every ambitious data scientist. Also, today we will look at an aspect that is commonly overlooked by a lot of the data science prospects. Yes, it is the portfolio of the candidate. The data science portfolio acts as a very vital tool to crack the interview.

Individuals often get perplexed in between a resume and portfolio.

A resume is a brief summary of your life, skills, and experiences over the years which is generally 1-2 pages long. Whereas, a portfolio showcases the collection of samples of your artwork, writings, images, and also tasks. Link to your online portfolio can also be added to your resume.

Prospects usually go with interviews with only the resume in their hands, and also the resumes are loaded with pointless details that are in fact not necessary. They don’t understand that the advantage of “show, do not tell” is a lot more persuasive when it comes to getting a job as a data scientist.

Now let’s look at how to develop a Data Scientist Portfolio?

Primarily, the Data Scientist portfolio includes a collection of data science tasks that you have actually dealt with, it showcases yourself and your data scientific research skills to the managers employing you for the work. So, it is about marketing your skills and talents. Your portfolio must speak “This is me, and this is what I can do for you”.

Take adequate time to develop your portfolio, it must create a long-term impression on the managers.

If you are a fresher then you ought to know about which tasks you can function.

On a completely different note, this tip could be for you:

Data Scientists and software developers in the real world are not ideal, they also use Google to get their issues resolved. If these people read your public work(blog sites, responses) and have their troubles resolved, they may think better of you and also connect with you.

” A Portfolio is public proof of your Data Science Abilities”, this meaning was offered by David Robinson, who is a popular data scientist today. One of the most reliable methods that helped him was doing public work. He was a go-getter on the Stack Overflow programming to address topics related to the data science field and when a Chief Executive Officer of the business was so impressed by his solution that he contacted him and David was hired after a few round of interviews! The more job you do, the greater the opportunity of an unusual case like this.

For an entry-level job also, you require to have a little real-life experience because that is the demand of many companies.

You might have seen some memes such as this on the internet. However, the genuine concern is how do you get experience if you need it for your very first job? The solution you are seeking is Projects. These data science jobs for resume developing might be teaching fellowships, thesis, public works that we discussed above, and the take-home projects.

You must find out about the Top Data Science skills prior to proceeding in advance

Tips To Create Your Data Science Portfolio

The chance of somebody locating your portfolio is through your resume. Hiring managers go through your resumes extremely fast, and you have just a couple of mins to make an impression.

1. Appropriate Length

Although it depends on the work you have actually done, try to keep it easy. There is enough room to include all your work in 2-3 pages. Try not to include objectives and conclusions, keep space for your skills, jobs, and experiences.

2. Suitable Coursework

It is the work that is performed by students for the purpose of discovering. List out all the coursework that you believe will be applicable to the work description.

3. Technical Abilities

Note down all the technological skills of yours that the job profile mentions. The abilities you are best at should be written at the beginning and the skills that you have yet are not the most effective at ought to align later.

Keep in mind, to ALWAYS rate yourself on your abilities. Words such as efficient and familiar have to be used to provide rankings, don’t provide yourself with numerical ratings.

4. Work Experience

It’s great if you have any type of experience, however, suppose you don’t? You have jobs, thesis, competitions, and teaching fellowships that you can include. These are substitutes for job experience if you are a fresher to put into your profile.

There are numerous data science-related internships including data analyst, data architects, Business intelligence analyst, data engineer, and others, not just data scientists. The internship should provide you with pertinent work and you should learn something from it. Some type of data collection, analysis, version building, or visualization is favored for a real job.

But why internships? Most significantly because companies wish to hire individuals who can start to deal with real stuff with minimal training as it is time-consuming and time is money in the corporate world.

” Do not talk, show it”. Having internships reveals that you are serious and also enthusiastic about work and also is not just another prospect who states, “I am a very enthusiastic data science profession and intend to discover more about it”.

6. Real-world Projects

Projects offer you an opportunity to obtain experience when you can not get it from internships. Normally speaking, 3 data science jobs suffice to cover the typical responsibilities for job profiles you want. Always, write up your projects in a structured manner.


If you want to reveal your abilities, participate in Kaggle competitions, and contribute to conversations. Connect your Kaggle account in the data scientist portfolio so that companies can see how many competitions you have participated in.

Work on Real-time Data Science Projects and display your skills to employers

7. Social media 

Blog post your work, that is, your writings, posts, answers, etc on social media so that you are identified. You can also read up about one of the most recent and also greatest developments/technologies used by specialists in the field to expand your understanding. It is a great way to connect with and follow specialists.

There are numerous sites where you can post your write-ups such as Medium, Quora.

Subjects on which you can discuss:

  • Discuss your understanding journey and share your mistakes.
  • Clarify technological principles to others in a less complex way.
  • Communicate the outcomes of your work with eye-catching visualizations and learning journey.
  • Discuss the various challenges encountered in the journey and also how you had the ability to fix them.


We wish these pointers for the data science portfolio were valuable. However, the more you practice, the better you get at getting things done. Due to the fact that there is never a minute where you stop learning. Construct a solid data science profile and make way for countless opportunities. As your expertise grows, your portfolio is also updated.

Now strong theoretical knowledge of data science is a key aspect to build a strong resume. At ZaraTech we offer self-paced online Data Science training program conducted by industry reports. Skyrocket your career by enrolling to our course!

Happy Learning

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