How to build and advance your data science career? Tap into the exciting data science career opportunities

As reliance on technology and data grows day by day, today’s economy is leaning more towards analytics. Currently, there is a massive demand for people who can mine and interpret these vast data to find trends in the data and gain deeper insight into what it all means. In short, the world is offering exciting data science career opportunities and it needs data scientists. But data science can be an overwhelming field and just thinking about it can leave you dazed and confused. With so many data science career opportunities to explore, you might find yourself wondering which is the right one for you and how to build your career in that role.

So, as a student, what do you need to know to tap into these exciting data science career opportunities? What do you wish you had known earlier? Here are a few tips to build and advance your data science career. 

Read on: how to choose right data science institute

Tips to build and advance your data science career:

1. Choose the right role

This is an important step that helps you build a solid foundation for your data science career. Data science is a growing industry and there are a lot of roles and specializations in the industry. Some of the growing roles include data engineer, data visualization expert, machine learning expert, business intelligence analyst, data architect, etc. It is important to choose a role and transition into the right one. So, you need to be clear about what you want to become, what path you must take to build your career.  

2. Select a tool and master it

A difficult choice that every student will face while trying to take advantage of a data science career opportunities is which language/tool to choose? It is crucial for students to have a deep understanding and in-depth knowledge about the tool or language that they choose. Many people will urge you to master programming, database, distributed computing, machine learning, visualization, experimental design, deep learning, and more. But it is not often necessary to learn all these concepts. In most cases, machine learning tools are a great base for learning data science. However, if you have not yet zeroed in on any tools, it would be better to choose any of the mainstream tools/languages to start your data science journey. Python, R, SQL, and Java are some of the important languages that you can consider. But whatever tools or languages you choose, the important thing you need to remember is to stick to it and master it. 

3. Focus on Practical applications

As a student, while you undergo courses and training to learn data science, you should focus on the practical applications and not just on theory. It is crucial that you understand the practical application of data science. One of the ways to do it is to participate in data science competitions and taking up your own data science projects to gain more practical knowledge. Try working on open data sets and derive insights. Even if you do not understand the concept or language completely, you can always get a deeper understanding at a later stage. 

4. Communication and connection

Once you’re clear on your roles and knowledge base, you’ll start attending data science interviews with confidence. But do not let this confidence cloud you. You may be technically profound and strong on your concepts, but communication is still important to ace the interview. In fact, this is where most students fail. Your communication skills not only help you clear interviews but also helps your professional career in data science as your role might involve presenting an idea to your superiors, communicating insights to your peers, and such. Gradually, once you’re all set on the job, try to grow your network by attending data science conferences, hackathons, etc. This helps you make your mark in the data science community. 

5. Find the right guidance

This might sound like simple advice, but this is perhaps the most crucial point to remember if you have to build and advance your data science career. Of course, data science presents exciting career opportunities and companies are looking for talented individuals, but without the right guidance, your growth will be stalled. As a student, you need to find the right guidance to support you all the way. Find a mentor who has successfully navigated in this field and follow in their footsteps. This would make it easy for you to tap into these data science career opportunities.

The demand for data science is huge and organizations around the world including big names like Apple, Microsoft, Amazon, Walmart, and more are looking for such people. So, taking the right steps is essential for success. As a premier business school in India, Praxis offers a 9-month full-time postgraduate program in Data Science. With our vast experience in business education, we offer students both the time to understand the complex theory and practice of data science concepts and the guidance from knowledgeable faculty who are available on campus for mentoring. We also have a well-structured campus placement program that ensures interview opportunities with the most significant companies in the field. 

Check our data science course in Kolkata and Data science course in Bangalore