According to Forrester Research, the demand for data science is not restricted to digital natives and large enterprises anymore.

With enormous volumes of readily available data, virtually every industry wants to leverage that information to personalize customer experiences. That means not only high-tech and software domains are benefitting from data science but also other sectors such as manufacturing, marketing, and education.

Machine learning and AI have also contributed to the meteoric rise in the popularity of data science. And it will continue to grow by 28% by 2020, an IBM study predicts.

According to Talent Supply Index (TSI) by Belong, India alone saw a spike in demand for data scientists across various industries by more than 400% in 2018. That creates an acute situation where the technologies exist but not necessarily the people with the right skillset.

So, if you are thinking of becoming a data scientist, the outlook is rosy. There is a demand for professionals who know data science. Keeping that in mind, let us explore factors responsible for driving its market:

1. Enables better decision-making

A significant aspect of data science involves communicating and demonstrating the value of an organization’s data. This, in turn, helps in facilitating improved decision-making processes across verticals through tracking, recording, and measuring performance metrics.

Since a data scientist helps in ensuring that the staff maximizes their analytical capabilities, they are considered a trusted strategic partner by the organization’s management. And that is what makes the job so valuable.

2. Reduces marketing expenses

In this day and age, if you don’t know your customers, you can’t scale your business at all. Until a few decades ago, manual processes would be applied to study consumer behavior by organizations to formulate their marketing strategies. Not anymore.

Today, by integrating data science, you can fasten evaluating your customers and finalize robust marketing campaigns promptly. Who wouldn’t want to take the help of data science when the insights are relatively error-free and real-time?

3. Identifies opportunities

For any organization, building a sustainable predictive model requires an upfront investment in resources. With data science, the payoff can be huge.

Data scientists are responsible for not just studying existing processes in an organization but also developing analytical algorithms. They can boost an organization’s performance by leaps and bounds.

Not just that, data science offers real-time insights on competitors, customer behavior, and user trends. This enables organizations to make faster decisions when it comes to acting on opportunities.

4. Cuts costs on logistics

Logistical expense reduction is a constant goal for most eCommerce stores. On average, the cost of product returns is 1.5x that of the actual shopping expense. Fortunately, by integrating data science, they can assess the possibilities of products being returned and take necessary precautions to reduce such losses.

The technology can find out which customer frequently returns products or identify cities that have the most product returns. These insights enable eCommerce stores to adopt a proactive approach and call customers for feedback.

This can help them to cut down on expenses in logistics.

5. Directs actions based on trends

A data scientist explores and examines an organization’s data. After which, they recommend certain actions that the organization must take to improve performance, better engage staff and customers, and drive revenues. The entire activity ultimately helps define company goals.

Without data science, it won’t be possible to make favorable changes based on trends or continuously improve the value derived from the data-in-hand.

6. Makes products smarter

Data science involves the use of machine learning, and that has enabled multiple industries to make better products tailored specifically to meet the needs of customers. For instance: the product recommendations that you see on most eCommerce stores offer personalized insights to the users based on their past purchases or browsing history.

This technology has enabled eCommerce companies to understand consumer behavior better and make data-driven decisions, which previously wasn’t possible.

7. Redefines customer success

You are probably well aware of the fact that data is heavily used to identify market opportunities, modify marketing strategies, and improve user experiences. But do you know that organizations often don’t leverage the predictive power of data?

For example, data-driven companies may rely on “audience performance” to define their marketing goals, which in turn  help them drive revenues. Oftentimes, such attributes are just limited to what organizations can immediately target and exercise, and not what they can forecast.

In such scenarios, employing the power of data science methodologies can help them put more customer attributes to good use.

8. Identifies real-time errors

Data science gives instant insight into errors that help organizations quickly mitigate the effects, especially in the case of an operational problem. The technology can save operations from falling behind or entirely failing.


According to News Cred’s Neil Barlow, the world’s largest brands continuously delight Wall Street investors and increase stock prices by being predictable. As a data scientist, you build predictive models that allow you to say, “I know.”

That confidence influences the transformation of your organization into a profit center. Wouldn’t you like that?

With Springboard’s Data Science’s Career Track, you can master the foundations of data science and choose your focus area: deep learning, natural language processing, advanced machine learning, and others.

The best part is once you complete the certification, you boost your chances of getting hired manifold. So, are you ready to transition into your dream career?