4 Data Science career trends job seekers need to know

Data Science refers to the science of extracting information from data.

Data Science refers to the science of extracting information from data.

Data science is one of the hottest fields right now. According to Google, the search of the term ‘data science’ has seen more than 300% increase in the last 3 years. If you are asking “Why” at this stage, congratulations! You clear one of the basic requirements of Data Science that is to stay curious at all times and keep digging till you understand why something is happening.

Here are some of the reasons why people are excited about data science and why more and more people are opting for data science at a time when multiple industries are getting disrupted.

Why is Data Science getting so much attention?

Data science refers to the science of extracting information from data. But, why is getting so much attention? When you look at broad fundamental trends, there are four underlying trends driving the growth in data science.

Let us quickly look at these 4 trends:

Trend 1: The amount of data generated in this Universe is growing exponentially

According to industry estimates, there would be close to 50 billion connected devices on internet by 2020. These sensors include smart watches, virtual assistants, CCTV cameras, laptops, smartphones etc.

Each of this device is generating data which can be used to extract meaningful business information. More than 90% of the data which exists in this universe has been generated in the last 24 months.

Trend 2: The cost of storing data continues to fall

Starting in 1980s, the cost of storing 1 GB of data used to be 0.5 million dollors. Today this cost would be a few cents and it continues to drop! So, all the data being generated by these sensors can be stored at a very low cost.

Trend 3: Computational costs continue to fall

So you are not only generating more data- you can also store it and then run computations on it. With faster chips packing more and more transistors, we are in an era where we can run computations unimaginable to even the best scientists a few decades back.

Trend 4: Cloud computing has enabled mass democratisation of computations

A few years back, if you had to set up a data science practice – you would have to buy your own servers. You would need to make this capital investment upfront. Also, as the amount of data increased, you would need more and more computations. So, you would end up purchasing a new server every few months / year.

These four trends are basically the fundamental forces driving the growth in data science and machine learning. They are disrupting multiple industries forcing people to think about new business models. This is why there is so much demand of data science professionals across various industries today.

So, if you are someone with an interest in Mathematics, Statistics or Computer Science, data science becomes an obvious choice in current scenario. This industry is going to only grow for the next 10 years, if not more.

Industry research shows more than 50,000 unfulfilled data science jobs currently!

How do you get into data science?

Start learning about data science and programming as soon as you can. It does not matter which domain you are in or what is your past experience. As long as you have good quant skills, love problem solving and have a lot of curiosity – you are a good fit with Data Science roles. Start by learning Python, basics of Statistics and Linear Algebra. Once you have done that – you can move ahead with learning Data Science algorithms and processes.

Apply, apply, apply! Data Science is actually an applied science and what better way to stake your claim than showing some applications. You not only learn how to solve problems using these tools and techniques, but also differentiate your resume from all those wanting to do data science but not putting in efforts in the direction.

Participate in a few hackathons and data science competitions. You can also pick up open data sets in the area of your interest to create projects and solve problems.

Participate in Data Science communities and look for mentorS, interact with data science professionals through meetups, webinars, slack channels and find a few mentors to guide you for the rest of your career.