Big Data

7 Tips To Start Your Career In Data Science

6 years ago
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How to start your career in Data Science

Data science is known to power up business value across industries like financial, healthcare, and technology. Professionals in this field empower the management to make better data-backed decisions and help unlock opportunities previously hidden. If you want to start as a data science professional then this field is extremely lucrative for you. However this move can reap rewards only when you approach your career in a strategic manner.

Interested to know of some handy tips when you are starting a career in data science? Then this post will help you

1. Examine the multiple roles in data science

The first thing you need to do is examine the roles that are available in the data science sector. Some of the key roles include machine learning specialist, data engineer, data visualization specialist and others.

Choosing the correct specialty is extremely important. You need to match your role with the work experience and the background that you have in your career. Hence, it would be wise to gather information regarding each and every role of the industry and match your qualifications and expertise to select the best one for yourself.

2. Obtain skills for the role

The next thing you should do is to start looking for the educational courses that can help you prepare for the role you have selected. For that, you need to take a course that suits your interest. The theories can help you learn the skills and prepare for the challenges of the career. But make sure you are selecting a reliable course to obtain the skills.

3. Get in touch with industry specialists

Surrounding yourself with experienced professionals is a great move to keep yourself motivated and grow continuously. Though it can seem a little difficult at the beginning, you will eventually start interacting with more and more specialized people.

You can start by interacting with the specialists on social media and indulge in a valuable technical discussion in your niche.

4. Merge theory with a practical approach

Data science is not only about technical theories. The practical approach is extremely important if you are looking for a long term run in the industry. You need to grow your practical knowledge of the work that is required in the industry. For that, you need to spend more time in practical applications through different working opportunities.

5. Work on your communication capabilities

Just because you are in a technical field, doesn’t mean that you should stop yourself from obtaining better communication capacity. The data science industry offers an immense level of positive career growth to the professionals with strong communication skills.

6. Gather resources for current trends

To stay ahead in the game, you need to present yourself as a modern and well updated professional. Only then, you can expect companies to put their faith in you. So, keep on gathering resources regarding the current trends. Also, join a peer group online where you can share knowledge about data science tools and resources – Reddit is a great place to start with. Also, attend webinars and online sessions that help you stay updated on the current trends.

7. Choose the right tool or language

Choosing the right tool or language could be a difficult decision, but we suggest that you use the widely used tool / language to begin with. In this way, it will also be easy to find resources and tutorials online. It is imperative that you understand the concept rather than focusing just the right tool. Start with the coding language that you are familiar with and slowly begin to build on it. If you are new to coding then you should prefer GUI based tools to get started off with.

Challenges will come your way. But amidst all this, it is your motivated approach that will help you in conquering all those challenges. So, keep on trying and making your way towards desired success. If you are an upcoming data science professional then these handy tips will prove to be vital in giving you a good foundation to a successful data science career.