How to Create a Data Science Portfolio to Get Hired as a Data Scientist

Posted by Sam Lucky on July 15th, 2022

How do you become a data scientist? A query that crosses every aspirant data scientist's head. And now, we'll look at a topic that most data science applicants sometimes overlook.

Yes, that is thecandidate's portfolio. A data science portfolio is a crucial tool for succeeding in an interview. People frequently mix up a CV and a portfolio. A resume is a 1-2 page description of your education, skills, accomplishments, and experiences from the last few years.

Candidates sometimes arrive for interviews with only their resumes in hand, and these resumes frequently contain unnecessary and irrelevant information. They are unaware that "show, don't tell" is a much more persuasive strategy when trying to land a job as a data scientist.

Build a data science portfolio

 A data science portfolio is essentially a collection of data science projects you have worked on. It serves as a resume for managers considering you for a position and highlights your data science skills.

So, it's all about marketing your abilities. Your resume should clearly state who you are and what you can accomplish for yourself. Make a Data Science Portfolio with a Funny Emoticon Statement about Data Science.

Spend enough time developing your portfolio to leave a lasting impact on the management. If you are a new employee, you should know the projects you can work on.

On a unrelated issue, you might find this advice useful:

Because they are not flawless in the real world, data scientists and software engineers also use Google to find solutions to their problems. These folks might have a better opinion of you and even get in touch with you if they read your published work (blogs, responses), which will help them solve their problems. 

David Robinson, a well-known data scientist today, defined a portfolio as "public evidence of your data science skills." Serving the public was his most successful marketing tactic.

Tips to Create Your Data Science Portfolio

1. The Right Length

Try to make it simple albeit it may depend on your work. All of your work should fit between two to three pages. Keep space for your skills, projects, and experiences; try to avoid including aims and conclusions.

2. Relevant Academic Work

It is the work that apprentices carry out with the intention of learning. Make a list of all the coursework you believe will be relevant to the job description.

3. Technical Expertise

List all of your technical talents that are mentioned in the job description. The skills you excel in should be listed first, followed by the skills that you have but are not the best at.

 Never forget to appraise your own abilities. Don't rate yourself numerically; use adjectives like adept and familiar.

4. Experience At Work

Although having any experience is ideal, what if you don't? You might include your projects, thesis, competitions, internships, and internships. If you are a beginner, you can use these in place of employment experience to add to your portfolio.

5. Similar Internships

There are several internships in data science, not just for data scientists but also for data analysts, data engineers, business intelligence analysts, research engineers, and others. You should receive useful work from the internship, and you ought to gain knowledge from it.

 For real work, it is preferred that you use some kind of data gathering, analysis, model development, or visualization.

6. Practical Projects

If internships are not an option for you, projects provide you with the chance to get experience. Three data science projects are typically sufficient to cover the typical job duties for the job profiles you are interested in. Always systematically document your projects.

Conclusion: 

I sincerely hope that these data science portfolio tips were useful. However, you get better at doing tasks the more you practice. The reason is that learning never stops. Create a solid data science portfolio to open up many opportunities. Your portfolio is updated as your knowledge base increases, and also, if you are interested in learning data science, I can suggest you thebest data science course in Dubai. Learnbay provides the best data science, AI and machine learning course with an IBM certificate.