How to Get Experience in Data Analytics without a Full-Time Job
Updated: Jul 6
There's a catch-22 when job searching. Especially if you are a new graduate or changing careers. Many jobs ask for experience. Even jobs labeled "entry level" (which means something different to every company). But you need a job to get experience but you can't get a job because of a lack of experience. I've been struggling with this as well. It's a tough place to be in. But there are a few ways to get experience without a full time job.
5 Ways to Get Experience
Below are a 5 ways to get experience:
None of these I listed are easy. All take considerable time to work on to get experience. These are helpful to people who don't have anything on their resume. I won't be getting into specific advice on how to put this on your resume. But you can put on these on your resume and/or LinkedIn profile.
What is freelance or freelancing? It is a person who works for themselves. They may take on contract work for companies but they are usually self-employed. Freelancers may work with many clients at a time and earn income from different projects.
For a data analyst this means you'd work with clients to: build dashboards, analyze data, clean and manipulate databases. Anything a full-time data analyst does, but working for yourself. There are generally two main ways to get freelance gigs:
Find the clients yourself
Get the clients to come to you
Finding clients yourself takes a lot of work but you can be specific about what projects you take on. If you're only interested in data visualization, then you'd search for clients looking for that service. Two suggestions on how to find clients: (1) see if your friends, family, colleagues, or acquaintances need your freelance work; or (2) go to local businesses and offer your services. There are other ways but these are suggestions.
The other method is to get the clients to come to you. You could build a website to offer your services and try to direct traffic there. Or sign up for a freelance website like Fiverr or Upwork. Sites like these let you build a profile and showcase projects. People can go to these sites and search for freelancers for projects they want completed.
Freelancing is tough. It's not easy work but if you're motivated and interested in getting hands-on experience working with stakeholders this is a good method. Also, if you do freelance make sure you have all your paperwork in order and pay the taxes where you live.
Another way is to volunteer your services for a non-profit or a business. This is like freelancing where you may need to go out and find "clients" but you are not charging for these services. While most businesses are hesitant to hire freelancers, especially if they are new, most of them will be open to free help. Finding clients is like how you would for freelancing. You can either go out and offer your services (for free) to local businesses. Or you can use websites where you can search for projects/organizations that need data help like Catchafire or DataKind.
I like to work with non-profits that help causes I care about. That's either in education or animal welfare. I like to volunteer for a few months as a regular volunteer, seeing how the non-profit works. Then I talk with a few of the employees/staff members and see if they have any data problems. Then I offer to help.
Volunteering is a great way to get experience if you can. You're working with stakeholders (the non-profit/business) and working on projects they need help with. The main downside is that since it's volunteering you aren't getting paid. If you need a source of income and need dedicated time to finding one this method may not be the best.
I've talked about this in depth. And if you're switching careers to become a data analyst I'm sure you've heard this advice. Projects are a great way to showcase your data analytics skills. This lets employers know you do have the skills necessary to do the job. For more advice on building a portfolio look at posts from people like: Matthew Mike or Ian Klosowicz. There's a lot of great data content creators to list but these are two that focus on finding a job in data.
Below is general advice on projects and building a portfolio. While there's no hard and fast rule for your portfolio. I'd recommend at least having three projects with each one focusing on a specific tool:
Another thing , you don't want to build a beautiful dashboard that has no purpose. Since you want to be a data analyst. The projects you should focus on insights gained from data and how those help you solve the business problem. For example think about how the sales dashboard can help a company grow their profit or increase their leads for the marketing team.
Since these projects are going to viewed by potential employers it's important to have your best work. You're likely going to have multiple projects since practice does make perfect. Once you've created a new project use it to replace one of your old projects. I've built over 10 projects but on my portfolio I only showcase the best 6 of them. Also, you don't want to overwhelm someone on your portfolio. I'd say at most of 6 projects should be on your portfolio. Employers doesn't want to search through 10+ projects to find one that they think is good.
For your portfolio have the following for each project:
Title of the project
Brief description of the problem you're trying to solve
The tools used
An image or a link to the project
Part time job
Another great way to gain experience is to get a part-time job. While you might not be able to find a full-time job as an analyst you may be able to find a part-time. This lets you gain experience in a working environment and it helps generate income. It may not be what you're looking for it is still an option to consider.
Benefits of this option are: it is in a professional setting; and you are being paid for your work from a company. One way to find jobs is to go on job sites like Indeed or LinkedIn. Another way is by networking with others who may know about these opportunities. You can network either in person like going to conferences or online using LinkedIn.
This is like building projects. Another way to show your knowledge is create content around it. It can be anything from Youtube videos to LinkedIn posts. Either way you are showcasing your skills in the industry. This is one way how Annie Nelson, a data analyst, was able to demonstrate her skills to an employer. She began on TikTok and built a following talking about data analytics.
Like everything else listed, this takes time. One of the biggest things about creating content is that your content needs to be seen. While you don't need to become the next "influencer" it is helpful having an audience. The bigger your audience the more likely a potential employer will see your content. Building content also helps improve your communication. It lets you get experience with marketing and building a personal brand.
I've been creating content for almost 2 years. First on my blog and then on LinkedIn. So I'm a big fan of this method but it does take time and it's a lot of work. It's also easy to get burnt out and feel like you found out of ideas. I'd recommend this method If you're interested in building your personal brand.
You can create content on a social media platform like Instagram or LinkedIn. Or you can use sites like Medium or WordPress to create your own blog. Choose any platform you think you can be consistent with. And remember each platform has its pros and cons.
These are a few ways to gain experience without getting a full time job. You can add all of these onto your resume. While there's a lot more to getting a job than having experience, this is a good start. As I said before all these methods take time. These are not quick, there isn't any for finding a job especially when you're switching careers. I've heard from many of my connections that their project or freelance work helped them get an interview.
Hopefully this helps. If you have any other suggestions on how to get experience as a data analyst without a full-time job feel free to email me at email@example.com.