By Katherine Olowookere

Sep 15, 2022

The finance sector was the first industrial sector to recognize and use Data Science to make important business decisions.

But today, the application of Data Science is no longer limited to the finance sector. Currently, Data science is being leveraged and used across industries to drive and bring transformative business results. Several industries and businesses now recognize the importance of harnessing the power of AI and big-data to improve decision-making, predict user patterns and analyze trends in real time.

About 80% of firms across the globe are investing a large part of their earnings into creating a skillful data analytics division thus hiring the smartest of people in the Data Science domain because these industries understand and can see how big-data can streamline their business intelligence processes, boost productivity and help them to better address the needs of their consumers.

This singular reason has made the Data science profession one of the fastest growing domains with over 88.3% growth in job postings and this number is expected to increase by 27.9% by 2026 according to the US Bureau of Labour. 

Many data science employment will be available for experts with the necessary data science abilities as a growing number of sectors and domains wait to be disrupted and improved by data science approaches.

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In this article, we will highlight the top 5 business sectors where Data Science is highly in use. These top sectors include Finance/Banking,  Healthcare, Advertisement/Marketing, Ecommerce, and Entertainment.

1. Finance and Banking

The finance sector is widely known to be a Data-intensive industry and this factor must have contributed to why it became the first business sector to understand and utilize the power of Data Science in 2001. There is no doubt that the financial sector has expanded significantly as a result of the use of data-driven approaches, data science tools, and algorithms.

Data science is mainly used in the finance and banking sector for Risk Analysis and Better Risk Management.

Financial data scientists create tools and dashboards to enhance investment processes as well as support and advise relevant departments inside the firm, including investment teams.

Most importantly, data science tools have helped financial institutions identify and deal with the issue of financial scams to a great extent.

Credit card fraud and identity theft have often been the most common financial crimes and it has been a major concern to financial institutions. Fortunately, the advancement of algorithms has led to an improvement in the detection of these kinds of fraud. Today, anomaly detection is more simple and more accurate because of machine learning. By receiving a real-time detection signal regarding irregularities in financial purchases, firms can quickly reduce their losses from fraud.

Other areas where Data Science and AI have helped and can help financial institutions to be more efficient in providing services to their clients include the following:

  • Customer data management and protection
  • Customer data analytics
  • Personalization of  customer services
  • Algorithmic trading
  • Loan appraisal management

2. Healthcare and Insurance

The healthcare sector is also one of the top fields actively using Data science to solve complex real-world health issues. Data Science and Machine Learning are actively transforming the health sector from new drug discovery to patient care.

The healthcare sector in India has been recognized to be the top creator of Data Science jobs in the past few years according to an AIM research. Data in hospitals and healthcare sectors are highly unorganized and very difficult to access. According to Statista, the amount of data generated yearly in the global healthcare industry is around 2,314 exabytes (1 exabyte (EB) = 10^18 bytes).

Therefore, hospitals currently seek data scientists and data analysts to assemble, organize and deduce meanings out of enormous data daily generated in the health sector.

Data science has made it extremely easy to manage and access information from electronic medical records, clinical trials, genetic information, billing, wearable data, care management databases, scientific articles, etc. In Europe alone, the efficiency obtained through use cases for data science and machine learning can save between 380,000 and 403,000 lives estimated by Deloitte.

The integrated use of Data Science and machine learning has helped in clinical care and in improving health. It has also helped in addressing complex health care problems.

Pharmaceutical companies now rely heavily on Data science and machine learning algorithms to simplify drug discovery processes.

With Data Science, insights from patient information such as mutation profiles and patient metadata can be used to develop models and find statistical relationships between multiple attributes. As a result, businesses can create medications that target the major genetic abnormalities.

Data Science has also helped the healthcare sector in areas such as

  • Medical imaging
  • Genomics
  • Predictive health analysis
  • Monitoring Patient Health
  • Tracking & Preventing Diseases and;
  • Providing Virtual Assistance

3. E-commerce and Retail

The e-commerce and retail industries are consumer-focused sectors that only thrive through increased personalization and relevance by using data to understand consumer trends and behavior.

The most significant use of Data Science in e-commerce and retail is in the suggestions for new items based on consumer purchasing patterns (socalled Recommendation Systems). This result is achieved through certain machine learning algorithms and deep learning.

Data Science has successfully helped retail businesses to understand consumers, therefore, creating a mechanism for personalized recommendations.

It has also helped the retail industry to :

  • Analyze market trends and consumer behavior
  • help users identify relevant products by examining their previous searches and purchases
  • Carry out Predictive analytics to enhance customer experience.

The demand for Data scientists in the e-commerce and retail industry keeps increasing because they bring in a great combination of skills ranging from data knowledge to technology skills, business acumen, and statistical analysis skills.

The top companies hiring for data scientists in the E-commerce and Retail space include: Amazon, Walmart, Home Depot, Shopify, Etsy, and many more.

4. Advertisement and Marketing

Consumer data will be the biggest differentiator. Whoever unlocks the reams of data and uses it strategically will win.” –Angela Ahrendts, ex-SVP – Retail, Apple Inc.

Data science is now being used more and more in digital marketing for analytical purposes.

The presence of several social media channels, web pages, CRMs, and search pages has brought about an enormous generation of data every day. A high level of business intelligence is needed to analyze such large amounts of data, and this can only be done with the proper use of data science approaches.

Data from consumer behavior helps marketers create targeted campaigns that match what a consumer likes and wants to see. Correctly analyzed data gives marketers knowledge of the messaging, images, colors, and other components that appeal to customers. Data science has also helped digital marketers in the area of content development and content creation.

A practical example of how Data Science is typically used in the marketing industry is when targeted ads show up on Facebook or Instagram after a user searches for something on Google. That's the back-end work of data science! Data science is accumulating a user’s rhythms and search patterns, then pitching ads for what a user may be interested in.

Employers in the advertising and marketing niche prefer to hire Data Scientists that come from a marketing background.

The top companies hiring for data scientists in the Advertising and Marketing space include: Google, Facebook, TikTok, and pretty much every other big company which has a serious marketing and advertising strategy in place.

5. Entertainment

The entertainment industry has greatly given attention to its scientific aspects in the last few years. Data scientists are essential for assisting organizations in making sense of the vast amount of information that streaming services, production studios, and traditional media corporations are gathering about production patterns, user viewing behavior, and post-production planning

Data science is used in entertainment to predict users' interests, analyze customer sentiment, personalize content and marketing and enhance customer experience.

Employers hiring Data scientists for these roles look out for unique combinations of technical skill, analytical acumen, and creativity—a love for movies and television will also be a plus here.

The top companies hiring for data scientists in Entertainment space include: Netflix, HBO, Apple TV, Disney, Twitch, Amazon Prime Video, Hulu, and many more.

Tools used by Data Scientists in these various business sectors. 

Although the way Data Science is applied varies across different industries, the tasks which Data Scientists are employed to do are often similar.  To successfully do these tasks and operations certain tools and technical know-how are required.

Generally, a Data Scientist needs to know

  • Programming Languages such as SQL, Python, and R
  • Statistics and Statistical Analysis
  • Data visualization tools such as Mathplotlib, Tableau, Seaborn, etc.


Data science is revolutionizing various business sectors in the world today. It has become a common tool to drive effective decision-making in all areas of an organization.

Data Scientists are undoubtedly in high demand in these industries and they are offering an attractive average salary.

Want to join this growing field?

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About O'Fallon Labs

In O'Fallon Labs we help recent graduates and professionals to get started and thrive in their Data Science careers via 1:1 mentoring and more.

Katherine Olowookere

Katherine is a content manager at O'Fallon Labs. She is interested in writing about a varioty of topics including careers in technology. Katherine holds a B.Sc. in E. Physics. She is passionate about personal growth and making young people become better versions of themselves through personal self development

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