Finding a job in any tech field is not easy; it is even more challenging in data science. But thanks to the internet and the ability to work remotely, a great option to develop skills, gain experience and earn money simultaneously is freelancing. Want to know what kind of freelance options are available for data science? This article will help you get the answer.
The demand for data scientists across all branches is high, yet, finding a job in data science can be challenging. If you’re new to the data science field, just finished learning the basics, built some projects, and are ready to apply for jobs, then this article is for you.
When we often think about jobs, the first thing that comes to mind is applying for some companies, universities (if you want to enter academia), or government institutes. However, almost always, all these require some experience and a rich portfolio.
If you’re new to the field and trying to get your first role, freelancing is a great option to start with and build experience. Being a data science freelancer gives you great freedom to choose your projects and be in control of your working hours and wage. It is also great for beginners looking for more practical experience by building real-life projects.
When you consider being a freelance data scientist, you will come across different projects you can apply for based on your preferences and knowledge base. You can use many freelancing websites to find projects, such as UpWork, Topal, or the LinkedIn Jobs finder with the job type “contract.” However, regardless of the website you use, there are a set of job categories you can apply for. This article will explore seven of these categories.
№1: Data visualisation
One of my favorite aspects of data science is data visualization. Visualising your data and results is an excellent skill to develop.
Many startups and individuals are looking for data scientists who can create efficient visualisation that can deliver the message of the data.
When you browse freelance roles for data visualisation projects, you will find requests to create interactive graphs and dashboards using a specific tool like Tableau, Power Bi, or according to your preference.
№2: Teaching
They say the best way to learn something and make sure you fully understand it is through teaching it. So, once you master the basics of data science and become comfortable with in-depth topics, you can offer to teach these topics to others who are just starting their journey.
Teaching goes beyond the basics; you can also teach someone the path to follow to learn a specific skill or mentor and supervise projects. For example, helping someone organise their projects will open your eyes to new perspectives and give you unique experiences.
№3: Data cleaning
The first step in any data science project is collecting and cleaning the data. Cleaning the data often refers to putting it in a format that can be used directly when implementing different algorithms. Data cleaning is one of those tasks that tend to be routine and boring.
As a result, some data scientists may hire others to do it to focus on analysing and modeling.
To get a data cleaning role, you need to have good knowledge of data manipulation, the ability to obtain the relation between the different columns, and how to spot anomalies and trends.
№4: Develop models
So far, we haven’t covered a role that will allow you to build a portfolio and practical data science knowledge. For example, another freelance data science option is designing, building, and developing data models.
You will need to implement machine learning, artificial inelegance, or big data algorithms to accomplish a specific task in such roles. This may include building bots, recommendation systems, or other data science applications. This kind of project can be very lucrative but may require a somewhat long time commitment.
№5: Research
If academia and research is the path you want to follow, doing freelance research projects may be an excellent option to get a preview of what you can expect when applying for full-time research positions.
This particular role; focuses more on conducting customer research to help design the model and extract the data. This often includes conducting surveys and analysing results and maybe creating prototypes, and proposing implementation solutions for specific problems.
№6: Consulting
So far, all the roles we covered can be done by any data scientist regardless of their experience level. This one, however, is primarily for experienced data scientists who work in academia or research. Consulting roles are often posted based on a particular topic. Clients often will ask you for feedback and maybe even perform some analysis.
This is one of the highest-paying freelance roles you can find, and you can set the hourly rate based on what you think fits
№7: Content writer
Last but not least, another form of teaching content writing. If you want to document your learning journey or teach a topic to others but don’t want to do it one-on-one, writing tutorials and articles may be the option for you. Many websites that post technical content always look for people who can communicate complex information in an easy-to-understand way. Writing blog posts and educational articles, in my opinion, is a very rewarding experience and a great way to prove your understanding of various topics.
When you change fields, you may ask yourself, “How can I gain experience and develop my skills to get the desired role?” One way you can do that is to start by taking on some freelance roles. As a freelance data scientist, you can choose the projects you work on; you can specify your wage and build a portfolio that you can then use to apply for industry roles.
This article went through some of the most common freelance data science-related roles you will find and apply for on different freelancing websites. Then, based on your preferences and goal, whether it be to build more projects, enhance your learning skills, or earn money, you can choose the roles that best suit your preferences.
