5 tips for aspiring data scientists
Varsity Career mapping Career decision making Career planning Data sciences Career in data sciencesSo, you’ve decided that data science is the field for you? It’s an exciting and fast-growing industry, but it’s also unique compared to most other jobs. Here are 5 tips to help you out.
Map out your goals
Before you begin working as, or even studying toward, becoming a data scientist, you’ll need to map out your goals in detail. When doing so, aim to answer the following questions: Which branch or branches of data science most interest you? What would be your ideal industry to work in? What work environment you’d prefer (corporate, start-up, own business, full-time or freelance)? It’s important to have an idea of your goals, in order to make the most of your time and money when pursuing training or a degree. If you need help mapping out your goals, check out the free Take a Girl Child to Work Day Online Programme for a step-by-step guide.
Learn, learn, learn
Once you’ve mapped out your goals, it’s time to choose how you’ll become a qualified data scientist. The degree or course you’ll pursue will depend on the goals you‘ve already mapped out. It’s important to look at the specific requirements for the industry and position you’re looking to enter into. Most data scientist positions will require an undergraduate degree in Data Science, Big Data Analytics or a similar major. However, there are more and more self-taught data scientists emerging- especially in the freelance and start-up fields. Here’s an article that breaks down each level of tertiary education, based on how relevant it is to a career in data science.
Find internship and job shadow opportunities
Even if you’re pursuing a data science degree full-time, internships and opportunities to job shadow a data scientist are valuable, and you should try your best to get involved with them. Not only will this boost your work experience and teach you valuable professional skills, it will also give you a clear idea of how data science positions look in the real world.
Network
It’s never too early to start building your professional network of connections in the data science field. There are so many ways to network online (on platforms like LinkedIn) as well as offline, such as on campus, through your peers and at industry workshops and events. Here’s an article on why networking is so important, as well as a few networking do’s and don’ts to keep in mind.
Commit yourself to learning
Data science is fast-paced and constantly evolving as new technology comes out, so even once you’ve graduated, you should still prioritise up-skilling and learning new things. You can always go further when it comes to mastering a data science skill, learning a new tool or expanding your skillset through online courses and resources. Doing this will put you in a league above the rest, and really boost your chances of landing your ideal position and becoming an expert in your field.
Data science is a great field to enter at the moment, full of growth and exciting opportunities. With a bit of planning, hard work and dedication, you too can become a part of it!