How To Advance Your Data Science Career: 4 Steps to Success

The use of the internet has grown immensely, be it for businesses or personal use. This change has brought a tsunami in data consumption and production. And the demand for professionals who can make good use of this data has also grown considerably. There are tonnes of opportunities in the field of data as of now. Earlier professionals who had technical skills were enough to manage things. But now, professionals are required to have both technical and tons of other non-technical and soft skills to achieve heights in their careers. 

For instance- Technical skills like data analysis and coding may be enough for entry-level roles; for higher-level roles, you must possess advanced skills like communication, critical thinking, strategy, and leadership.

How To Prepare Yourself for a Successful Career in Data Science

Making a career in data science is as easy as earlier anymore. The competition has increased considerably. So, this is the time to give up the old-school approach and practice every possible tactic out there if you want to see yourself as a big shot in the data industry. Anyways, without further ado, let me start listing out five steps to help you advance your career in data science. 

Don't only depend on a single course.

Whenever anyone starts their journey, they usually enroll in a course and assume that that single course is enough to learn everything. But that is not entirely true! In my opinion, you should frame your coursework in a way that you can do everything. 

Try enrolling in complementary micro-courses to increase your knowledge. It would be much better if you opt for niche courses. 

Explore hands-on learning opportunities.

This is possibly the most crucial step regardless of what career path you take. And especially in data science, where you are required to have a high level of technical knowledge. 

Learning is of no use if you can't apply the skills outside of the classroom. Consistently implement your theoretical knowledge on projects if you really want to learn in a correct way. It is scientifically proved that practical implementation is the key to long-term learning. 

So, make sure that you are implementing everything you are learning simultaneously on real-life projects. 

For sample projects, you can gather data from various social media pages and analyze user behavior.

Grow your professional network.

No matter how good of a data scientist you are, it really doesn't matter unless enough people are or companies, to be precise, are aware of your talent. And how do you let people or organizations know about your talent? It is done through a process called networking. 

Right from the moment you enroll in a course, start finding more and more networking opportunities. Attend hackathons, seminars, meetups and join communities and peer groups. These things will immensely help you connect with people who are already settled in the industry. 

And the major benefit of networking is that it will help you land a job without putting in much effort. Yes, according to research, almost 70% of positions are filled through networking in today's time.  

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Start a Side Project

If you ask me, this is the best ever advice anyone can ever give to you. Starting a side-project is undoubtedly the best way to improve your data science skills. 

To do this, you can use various platforms like Kaggle or GitHub. 

The best part about these platforms is that you can find tonnes of data sets posted by companies and researchers and make use of them for various purposes. On top of it, you can find a lot of like-minded people who are always there to help you out, give ideas, and constructive criticism. 

It will also help you to build your portfolio that you can show in your interviews. Plus, having a side-project in your portfolio or resume will show the employers that you have the drive for self-initiative. 

Conclusion

I hope these tips will help you at least a bit in your data science journey. One more thing I would like to add is- Always stay updated with what is going on in the industry, watch interviews of famous data scientists and read more and more books on data science. Data science is a field that will face many changes in the coming time, so make sure that you are not left out of the game.