03-Jun-2021 17:38:48 pm
Are you looking for a career that’s interesting, challenging, and very much in-demand?
A data scientist career ticks all these boxes and more. Keep reading for the ultimate learning path guide detailing the skills, knowledge, and training you need to become a data scientist.
Firstly, you will need some technical qualifications. The most common route is to study for a bachelor's or master's degree. In fact, 88% of data scientists have a minimum master's degree, and 46% have a Ph.D.
To get the most of the skills and knowledge needed for a data science job, you should study for a degree in math and statistics, computer science, or engineering. Other qualifications may be sufficient, but these are the most common.
Alternatively, since there is a shortage of data scientists, more and more companies compete with people who do not have formal qualifications. Without a formal degree, you'll need a fair amount of experience in a relevant role, such as a computer programmer or engineer, or be able to demonstrate strong math and computing skills. You will also need to complete some specialist courses.
These days you can find fully certified courses online that are taught by experts in the field of data science. E-learning platforms have become the best way to acquire specialist skills at an affordable cost, and are overtaking formal educational institutions as the number one way to gain in-depth knowledge and skills.
As well as competency, you must be able to demonstrate specific skills and specialist knowledge.
Many people earn a master's degree in data science, but there are other routes you can take to gain relevant knowledge, such as e-learning courses. Depending on the requirements of the role you want, you may need:
In terms of non-technical skills, the following are usually high on employers’ lists:
During and after your studies, it's a good idea to get some work experience.
You might be lucky enough to find paid work for any business that needs data scientists in industries including finance, retail, manufacturing, and engineering. Nonprofits and charitable organizations are a good place to look if you are struggling to find work experience, although you may have to settle for unpaid work in these areas.
Another way to gain valuable experience in the field of data science is to enroll in courses that hold workshops as part of the curriculum. Udemy and SuperDataScience courses offer real-life, practical activities that allow you to build your experience level.
The variety of specialist projects is too many to list in full detail, but here are some examples to whet your appetite:
It's helpful to build a professional portfolio that includes a few different types of successful projects, so don't be afraid to try a few different specialties. This is especially true if you're not sure which feature to focus on initially. Following the above steps will empower you for a successful career in data science or business analysis.