The Value of a Data Scientist

CJ HaugheyCJ Haughey | 9 minute read | April 8, 2019
data scientist roles

In this article

Data is the new oil. You may have heard that before, but despite the obvious impact of data science on the world today, it sometimes seems like there is relatively tempered buzz around the actual role of data scientists in business.

The reality is, data is worth very little if you don’t have highly skilled professionals who can derive actionable insights from it. A lot of companies still don’t truly understand the benefits of a data scientist, which means some businesses are still diving into data with virtually no idea of how to use it properly.

Big mistake.

It’s estimated that data volume will grow to 44 trillion gigabytes by 2020, but as most of that is unstructured data, many companies won’t be able to put it to any use.

Unless they hire a data scientist.

In this article, we’ll reveal the value of a data scientist to your company, going beyond the benefits of data science to show you exactly why you need a data scientist to tap into the real potential of this enigmatic aspect of modern business and marketing.

Let’s dive in.

What Does a Data Scientist Do?

Before you can fully understand the importance of data scientists in business, you need to know what a data scientist actually does.

Data science jobs have evolved over the past decade in line with technological advances, but the core principles of the role have remained the same. The primary purpose of a data scientist is to discover valuable insights from huge amounts of data, which can then be used to shape company strategies and achieve business objectives.

Typically, data scientists will have a solid grounding in:

  • Math: When data gets large, it often gets unwieldy. Data scientists need to use mathematics to process and structure the data they’re dealing with.
  • Statistics: Statistics allows data scientists to slice and dice through data, extracting the insights needed to make reasonable conclusions.
  • Programming: A data scientist needs to know several programming languages to achieve specific goals. For example, SQL to extract data from relational databases and Python for writing scripts for data manipulation, analysis, and visualization.
  • Analytical thinking: A lot of data science involves solving problems. Data scientists have to be adept at framing those problems and methodically applying logic to solve them.

They may enter the industry as a graduate on the back of a data science degree or they could be a software engineer or computer analyst changing career paths.

Today, data science is one of the hottest career paths in the world, with demand for data scientists growing 29 percent year on year, growing almost 350 percent since 2013.

As more businesses wake up to the value of data science and analytics-driven marketing, more people want to know how to become a data scientist.

Get To Know Other Data Science Students

Ginny Zhu

Ginny Zhu

Data Science Intern at Novartis

Read Story

Brandon Beidel

Brandon Beidel

Senior Data Scientist at Red Ventures

Read Story

Aaron Pujanandez

Aaron Pujanandez

Dir. Of Data Science And Analytics at Deep Labs

Read Story

8 Benefits of a Data Scientist for Businesses

Now that you know what the job entails, it’s time to look at the value a data scientist can bring to a company. Business owners may wonder why they should hire a data scientist, whereas people considering the data science career path may wonder what they can add to a company with their data science skills.

Let’s find out.

benefits of a data scientist


1. Data Scientists Empower Management to Make Smarter Decisions

In modern companies, a data scientist is not “the IT guy” that you go to with minor computer issues. Data scientists can rise high in the organization, establishing themselves as a trusted advisor among C-suite members. (Ninety percent of large organizations are predicted to have a chief data officer by the end of 2019.)

With their expert insights, they can guide management and help craft the organization’s strategy in key areas, including sales, marketing, and customer relations.

As one of the largest oil companies on the planet, Shell faced major difficulties managing its vast resources and drilling machinery all over the world. Quite often, the company would lose a small fortune in a single day because of machine downtime.

Once Shell invested in data analytics, it placed its trust in data scientists to combat the problem. Using a host of software and predictive analytics, the team was able to monitor machine performance and understand when inventory needed to be replaced.

2. Data Scientists Make it Easier to Achieve Business Goals

Imagine playing a game of chess that didn’t include the kings. It wouldn’t make sense, as the ultimate goal of the game could never be accomplished. Businesses bring data scientists in specifically so they can help the company achieve its goals.

By giving a data scientist the freedom to explore all of the company’s data, it’s possible to maximize potential. With their expertise in data analysis, the company will be able to pick up on trends before they go mainstream, or figure out the best ways to engage their customers.

One example of this is in merchandising and branding, where data science is used to evaluate customer interest in different types of packaging. You can use this to enhance the visual appeal of your products.

Netflix uses this technique successfully, combining machine learning and data science to find the most engaging artwork for each of its offerings. Generating increases in audience engagement and profits are among the biggest benefits of data science.

3. Data Scientists Improve Recruitment

Many companies struggle with recruitment, with 52 percent of leaders in talent acquisition claiming the hardest part of their job is finding the right people among a large set of applicants.

LinkedIn has been using artificial intelligence (AI) and data to help connect employers with prospects for a few years now. This is just one example of how data-driven recruitment is on the rise. What companies must realize is that such techniques aren’t limited to job boards and recruitment agenciesyou can use it in-house.

Nobody wants to spend their days sifting through resumes. With a data scientist in the company, this kind of chore becomes a thing of the past. Data scientists can gather information from various job sites, social media platforms, and corporate databases to streamline the recruitment process. This way, businesses that need new personnel will find it easier to make faster and more accurate choices.

4. Data Scientists Challenge the Workforce to Embrace Data

One of the biggest benefits of a data scientist is that they can become a leader in a company’s digital transformation. It is their responsibility to bring other staff members up to speed with data processes and practices, and they must show everyone how data can be leveraged to get actionable insights.

Forbes revealed that almost 60 percent of companies believe the biggest challenge in customer data analytics is the current skill level of their employees.

Digital transformation requires a company to re-evaluate everything on the inside of the company, which requires wholesale changes to practices, infrastructure, and technology, as well as huge investment in training and recruitment.

Data scientists are instrumental in this shift, as they can help to create a culture of data from the top down, helping management understand the benefits of data science and the need for it to be adopted throughout the entire organization.

When this happens, more employees are exposed to data, which encourages greater collaboration and offers more perspectives to provide fresh insights into the challenges the company is facing.

the value of data science


5. Data Scientists Refine Target Audiences

Any course in Business 101 will explain the importance of defining your target audience. If you don’t know your customer, how will you sell to them?

In the digital age, if you don’t have a clear understanding of who your customers are, you’ll struggle to connect with them at all, never mind convince them to purchase.

Luckily, when it comes to data, there is an embarrassment of riches for marketers to work with, which makes it possible to create detailed buyer personas for a target audience. For example, you can find customer data from:

  • Google Analytics
  • Social media
  • Email lists
  • Customer surveys
  • Online forums

However, this data will count for little if you don’t have a data scientist. This is where the value of a data scientist really makes the difference, as they can help companies pinpoint consumers who are a perfect fit for the products and services on offer.

The Harvard Business Review reported on how the clothing company Stitch Fix hired 80 data scientists to forge connections with their audience. By putting data science at the heart of the company, Stitch Fix found the people for their products, and annual profits soared toward $1 billion.

6. Data Scientists Make it Easy to Test Multiple Ideas

Quite often, companies will have more than a few good ideas on the go at any one time. The marketing team may be undecided on which channel is best for their audience, and the CEO may be sticking an oar in with some left-field suggestions.

Having a data scientist around is helpful as they can run the numbers and determine the impact of different decisions and initiatives within the company. This makes it easier to quantify the success of the company’s efforts.

For example, let’s say your business wants to build up an email list. HubSpot split-tested two ideas by offering a lead magnet at the end of their blog posts. Some blog posts had a link to the separate landing page, whereas other posts had the form embedded within the post—an in-line call to action (CTA). The value of a data scientist was proven here as the in-line CTA generated 71 percent more subscriptions.

7. Data Scientists Identify New Revenue Opportunities

Research from McKinsey asserts that data will help retailers generate a 60-percent profit-margin increase on a global scale.

It is the nature of data scientists to always look for more. They are never satisfied with the current situation. Data scientists continue to question existing methods and push the boundaries of analytics in the quest to get more value from data. That attitude will help businesses expand and scale over time.

Recognizing the value of a data scientist, Mastercard set up Mastercard Retail Location Insights to analyze the performance of economic areas within local communities. Data scientists analyze secure transaction data collected from over 2 billion cards to get insights on revenue performance at a street level. This helps Mastercard identify new opportunities within city centers so they can set up new commercial ventures that will deliver a ripple effect in business throughout the local area.

Data scientists can help any company analyze its existing market in this way, making it possible to discover new revenue streams.

big data advantages


8. Data Scientists Save Companies From Major Risks and Losses

If your company embraces data-driven marketing, you have the potential to understand your customers on an intimate, one-to-one level. This begins with consumer data such as age, gender, and location. When you dig a little deeper, you can gather data about onsite behavior, analyzing how long visitors spent on your website, what pages they visited, and which products they viewed.

This form of marketing and research allows companies to leverage one of the best benefits of data scientists. No longer do businesses need to take risks or make uneducated guesses about what will work. Instead, they can make decisions based on quantifiable, reliable data insights.

We can find a perfect example of this by looking at the use of data in the healthcare industry. Drug development is an arduous process that often takes years of research and testing, and around $2.6 billion before reaching the market.

With data scientists in play, companies can:

  • Harvest vast reserves of biomedical data obtained from treatment results, numerous tests, and case studies.
  • Use advanced algorithms to create simulations of how drugs would interact with specific proteins within the body.
  • Determine the efficacy of the drug and predict success rates.

This would slash costs and the time involved in drug development. Furthermore, the risks of failure would be minimized, making the entire process a much more profitable and worthwhile endeavor.

The Impact of Data Science Is Only as Good as Your Data Scientists

Nowadays, technology is developing at breakneck speed, with AI stealing most of the limelight in many different industries. However, the real gold is what lies behind the fancy robotics and cool apps.

On the surface, the statistics and analytical tasks in data science may not seem as exciting as other tech careers, but it is the indispensable foundation on which revolutionary AI, machine learning, and blockchain ventures are built.

Without data, our world wouldn’t have a digital age.

And without data scientists, companies can’t hope to survive digital transformation.  

The impact of data science is obvious. However, more companies must realize the true value of a data scientist in this era before it’s too late.

Since you’re here…Are you a future data scientist? Investigate with our free step-by-step guide to getting started in the industry. When you’re ready to build a CV that will make hiring managers melt, join our 4-week Data Science Prep Course or our Data Science Bootcamp—you’ll get a job in data science or we’ll refund your tuition.

CJ Haughey

About CJ Haughey

CJ is a journalist, creative writer, and self-described digital marketing nerd who is currently studying data analytics.