By Fatima Haroon
Sep 24, 2022
“How do I get a job of Data Science when I don’t have prior experience?”
“Every company I apply to asks for 1-2 years of relevant experience, and I don’t have any. What should I do?”
These are some common fearful questions clients and students share with O’Fallon Labs. Of course, most jobs in data science require years of experience in the field. But most of us need that first job to gain that experience.
These possibilities make it challenging and complicated for students to break into the field of data analytics. So, how will you break out of this nonsense loop? The simplest answer is your skillset and how you portray it, i.e., through your portfolio.
You can’t expect success in your data analytics job interview if you don’t have a portfolio. Instead of getting discouraged, here are my top suggestions to help you get your first data science job within a few months.
1. Complete an End-to-End Data Science Project - Design Your Portfolio
If you have recently graduated with your data science degree or taken data analytics training and switched careers, you must show your skills. Data science is a vast field with in-demand skills.
This field is all about solving problems by collecting and analyzing data. Why would an employer hire you if you haven’t proven your skills by solving problems or drawing conclusions from your accumulated data sets?
The best way to prove yourself is by working on an end-to-end Data Science project that demonstrates your impeccable problem-solving skills. It’s typical of the IT industry to demand portfolios to check the quality of the individual’s work before hiring them.
Therefore, when you work on your portfolio and build projects, you exude the innate curiosity and drive that employers look for in a successful data scientist. But remember, the projects you choose to work on should be unique. You should be able to confidently talk about the methodologies and results gained by them. This will help you ace your job interviews.
Consistency is the key to your success. Always be focused on your projects. Plus, the internet has thousands of free data sets that you can work on. Just google Kaggle and start building your portfolio.
2. Become a Freelancer - Start Selling Your Services
Freelancing is another way to build your portfolio. With freelancing, you sell your skills learned from the data analytics courses you took. However, it’s an excellent alternative to gaining experience while waiting for a call-back from potential employers.
The best part is that you can have flexible hours for work. You wouldn’t be bound by contract or long-and-tiring hiring processes when you do find a job. Plus, you can quit any time! Now it is on you whether you sell your services as a data scientist or give data analysis training classes; the choices with freelancing are limitless.
Always stay focused no matter what kind of project you choose. Work hard, be creative, and avoid distractions. The more you do this, the more you will achieve. That’s a guarantee!
3. Become a Data Scientist Writer - Showcase Your Knowledge
Data scientists manipulate data. This makes them natural storytellers as they can turn extensive data sets into impeccable visuals to explain their findings effectively. Writing about your projects eloquently demonstrates your communication skills and the ability to lure in readers.
Your blog or research papers will beautifully define your soft and hard skills to your potential employers. Therefore, start with platforms like Medium or buy your domain and start blogging.
During your blogging journey, you’ll learn how to explain complex terminologies in simple words to attract a broader audience. This not only makes you a greater communicator with a deeper understanding of data analytics but also makes you a great data scientist.
4. Networking - Gain Visibility
Your network is your net worth! This is a famous quote that describes the significance of networking. Remember your portfolio? Well, upload it on GitHub. Then create your LinkedIn profile and share that online portfolio link there.
These are great ways to gain visibility. You need to build an online audience that will vouch for your skills. Writing online also gives you an edge over other data scientists because you’re making a name for yourself.
You’re building a brand - a brand visible to everyone. Platforms like LinkedIn and Medium are goldmines where you can connect with millions of people, share your projects and findings, and gain clients and jobs.
Interact and engage with like-minded individuals through comments and posts. Get to know people and your community, and give them a chance to get to know you professionally. Be active and consistent. You may get overwhelmed by the results. Who’s to know? Your potential employer might be one of your connections from LinkedIn.
5. Get Training - Work with a Mentor
Every successful individual has a mentor that helps them reach success. At O’Fallon Labs, we help individuals like you get their first ever data science job. In fact, we’ll help you learn data science the right way here!
We will teach you all the tips and tricks no one told you before. From building a powerful resume to preparing for your data science job interview, we will be there at every step. Your career’s success starts right here with these successful steps you must take to become a data scientist.
Conclusion
A lack of work experience can affect your data analytics career. That doesn’t mean you can’t gain experience in other ways and get a job. In fact, it’s the opposite. Tons of opportunities await you in the data science industry with these proven tips and tricks and our coaching services. Let’s begin this journey of success together!
In O'Fallon Labs we help recent graduates and professionals to get started and thrive in their Data Science careers via 1:1 mentoring and more.
Fatima Haroon
Fatima is a professional writer with 5 years of experience in the SEO Blog Writing and Copywriting industry. She uses industry's best practices to write converting and compelling copies for global clients. In O'Fallon Labs Fatima supports the clients with identifying the key pain-points of our clients and
create original content based on our offered solutions.