5 Ways To Build A Winning Data Science Portfolio That’ll Get You Hired

The world of data science is booming and is creating a tremendous amount of job opportunities. Today, the number of people with top data science skills are increasing rapidly — people are gaining knowledge, learning more and more about the domain. However, there is still amiss — while a resume is important, a significant number of data science professionals and enthusiasts have not yet realized the importance of a project portfolio. Gone are the days when “Bachelor of science” on your resume would act as a catalyst in landing you a job; in this ever-competitive world of data science, you need real-time experience and a portfolio that showcases that. In this article, we are going to see why a portfolio is important and how a data science professional can create a project portfolio that would make an impact.

Significance Of A Portfolio

A portfolio is way more effective than a resume. While a resume only acts as an element that introduces you, a portfolio showcases your work, your skills, and your abilities. A portfolio is evidence of all the work and projects you have done. While many data science professionals across the globe are busy applying for jobs, a portfolio can make it easier — it has the power to make you visible in the industry, and if your projects mentioned on the portfolio is strong enough, it would even provide you with some of the best opportunities. So, being a data science professional make sure that you have a strong project portfolio with a bunch of top projects you have done in the past.

This Is How You Can Build Your Data Science Project Portfolio

1. Projects Play The Vital Role Here

The Data Science domain is one of the most lucrative yet vast fields of work. One needs to have a lot of knowledge as well as experience. But what if you are just starting out in the industry? How would you get that experience that is required to land you a data science job? The answer to that is “projects”. Today, almost every data science enthusiast optS for a data science course before landing in the industry and hunt for a job. And there are many data science institutes that also let its students carry out projects while studying. Furthermore, one can also carry out personal data science projects. Seek help from others from the industry and do projects. The better the projects you have in your bag, the more you gain real-time knowledge and the more you get to showcase your skills. And that is what the industry looks into a candidate — knowledge and skills and the ability to take charge. Word to the wise: Do not pick up any random project and do it. All you need to have is about 5 projects that are relevant to the job role of a data scientist.

2. Freelance Your Skills

This might sound very generic, but it is one of the best ways to get noticed in this competitive industry. Even though the data science industry is booming, the number of professionals are still not incredibly high. That is not all, it is also an expensive domain as it delivers a lot of value, and not every company (especially startups/new-born companies) can afford to have a data scientist. Being a data science professional, if you proactively reach out to these companies and offer your skills and knowledge and help them, it would make your portfolio stronger. Also, it gives you a platform, a public profile, a profile that gets noticed in the industry. So, don’t hesitate to work for free if required, as it has other perks too. Word to the wise: Getting noticed and praised might be intriguing. However, that doesn’t mean, you keep working for free. The bitter truth is you need money for your bread and butter. So, work for free until you set yourself apart from others and set a tag your precious skills.

3. A Personal Blog Or Website

When it comes to showcasing your projects and skills, an online presence is a must. There was a time, not everyone could have a website. However, those days are gone; there are several free website building platforms are available online. All you need to do is pick a template and create one — there is no rocket science. You can also have a dedicated blog for your work where you write about the projects you have completed, or you can share your knowledge. Having a website as a portfolio is considered to be one of the best strategies for a top-notch portfolio. Word to the wise: Looks matter. Make sure, your website is not just another random website on the internet. Make use of the best templates available and try to make more data science-centric.

4) A GitHub Profile

One of the best online platforms on the internet today, GitHub over the years have tremendous popularity. If you have solved a problem and you want people to see it how you have done, there GitHub without a doubt should be your first choice. Whether it’s a code or just a write-up, leave it on GitHub and share the link with others. There are many companies across the world that actively look at GitHub profiles to make sure whether the candidate is genuine and competent professional.

5) Medium Blog

Today, almost every company has its Medium account. It is considered as one of the best blogging platforms. If you are interested in sharing your data science knowledge, you can always make with Medium as the platform actually justifies its name. Also, Medium has a significantly huge community that helps you grow not as a general blogger but as a blogger from a specific domain. So, if you are a data scientist who is building its portfolio, make sure you don’t forget to tap in Medium.