How to Stand Out as a Junior Data Scientist

7 things you can do to show your skills even if you have no experience at all

Every junior data scientist feels frustrated when looking for their first job and has nothing to show for it. This post will suggest 7 ways to demonstrate your knowledge of data science before your first interview.

Open code contributions

At first, joining open-source projects seems to be a daunting task, but it is not necessarily the case. There are many projects on GitHub and other sites that are made for beginners, all you need to do is look for ‘good first issue’ tags. Most of these tasks are straightforward and easy to understand, so it is perfect for beginners.

First Timers Only: The platform where people who have never contributed to open sources can come and learn more and possibly be able to complete tasks.

Up For Grabs: Curated projects with beginner-friendly tasks.

Awesome for Beginners: A GitHub repository listing open-source projects that welcome beginners.

Even small contributions, like fixing a bug or adding to documentation, can show off your technical skills. Plus, it’s a chance to collaborate with others and learn how real-world projects operate.

Volunteering

Volunteering is always good, especially if it leverages your unique skills. For a junior data scientist, it is an opportunity to shine, grow professionally, and contribute to society. You can address real problems with real challenges from the field that are difficult to learn theoretically. That’s exactly what juniors are missing. These experiences of seeking challenges and striving to build good systems enable one to build a stronger technical portfolio that crosses global geographical boundaries. Working as a volunteer means you will also meet other professionals who think like you remember your name, collaborate with you, and recommend you as a colleague for one of their jobs in the ever-change data science competitive world.

Hackathons

A hackathon is an event that is typically held for anywhere between one to three days in which teams are created with the objective of problem solving or finding solutions. Look at it as a contest of creativity where the participants have to reach some objectives within a specific time period, for example, to design a certain model, an idea for a product, or even a working model of the specific product.

Most data science hackathons have endorsements from technology companies. These companies offer support in the form of mentors, tools, and even databases that one can’t easily get access to. It is a great environment to challenge yourself, work in a stressful environment, and be creative.

Hackathons are also a good way of interacting with other data scientists. I have been to a few hackathons, and I always make it a point to approach people and ask them what they do and if their company is hiring. Before the event ends I try to send connection requests on LinkedIn to the people I met to keep in touch with them.

GitHub

GitHub is a cloud-based developer platform that allows developers to create, store, manage, and share their code [1]. Juniors can use this platform as a portfolio that showcases their professional skills. I recommend that juniors put projects, course exercises, and notebooks with code in areas of interest where you have examined how the algorithm works on GitHub in an organized manner. GitHub is a place where people work, and not everything has to be super organized and clean. It is recommended to grow GitHub over the years and include a link to Git on your resume, so potential employees can easily reach it.

Medium

Juniors can publish articles on Medium on topics that interest them in the field of data science. For example, posts that explain complicated algorithms, posts about new tools, or new libraries including code. Again, you can add a link in your resume to your bio that points to your Medium profile. If you write a post with code, you can put the code on GitHub with a link in the post. This way, you can show potential employers what your interests are. It is very rewarding and can boost your self-confidence when other data scientists start following your blog and applauding you.

LinkedIn post

Many people think LinkedIn is just for applying for jobs, but it’s so much more than that. It’s where you can really start building your professional presence. Post about the projects you’re working on, share lessons you’ve learned, or even comment on industry trends.

Don’t be shy about using hashtags like #DataScience or #MachineLearning — those can get your posts in front of more people. Oh, and don’t forget to engage with others. Commenting on posts or starting discussions can help you connect with people who might help you land your first job.

When you write posts on LinkedIn about your professional field, the algorithm rewards you with a higher SSI score. You can learn more about the SSI score on LinkedIn’s website. Similarly, the algorithm will penalize you if you write about topics that are not professional, such as politics or anything personal.

Remember, this is SSI, and you are the product! Don’t compromise the quality of the product.

MeetUps

For junior data scientists, attending meetups is a great way to interact and learn from industry professionals, and learn about the latest trends. It’s different than online networking because it allows meeting people in person which makes it more legit. Saying a few words like your name work experience, and the job position you’re targeting would be helpful in creating an impact. Look for people, especially those who seem to be isolated and eager for company, ask them how they got into data science, and tell them your professional story, and that you are looking for open positions. These conversations may result in receiving a recommendation, being mentored, or learning more about the world of data science.

Summary

Even if you don’t have work experience, you can still showcase your practical skills as a data scientist. The key is to do and pitch your work effectively. If you complete a project but don’t pitch it, it’s as if you never did it.

For example, I recently worked with an analyst who had done some modeling at his job but hadn’t presented it effectively. We updated his resume to highlight his achievements and encouraged him to attend a meetup where he pitched his work to relevant people. This proactive approach led him to start the hiring process for this company.

The lesson? Do (Open code, Volunteering, Hacatons) and pitch your work and share it with the right audience (GitHub, LinkedIn, Medium, MeetUps). Good luck to everyone working toward their goals!