Updated on 21 Sept 2022

The Best Industries for Data Science Specialists

Aleksandra Yosifova Published on 21 Sept 2022 4 min read

Data science is a multidisciplinary field combining math, statistics, and computer science with business insights. The term was coined in finance, so naturally, it has been associated with this field for a long time. Today, it has spread everywhere. But thanks to its broad scope, you can apply data science to almost all industries.

While this creates more opportunities for data scientists and businesses, it also increases the scope of knowledge and capabilities specialists need to succeed. Apart from analytical and technical skills, you need a good understanding of the chosen industry for your data career – from basic terminology to the latest developments.

So, although it isn’t necessary to know which field you want to work in at the beginning of your career, it’s helpful to narrow down your choices.

Not sure where to start?

To help you navigate the complex world of data science, we present a brief overview of different types of industries where it’s used.

Read on to learn what the work of a data scientist looks like in different settings. Some sectors in our article are expected, such as Big Tech and cybersecurity; others might surprise you.

Eight images representing the best industries for data science specialists: healthcare, oil and gas, big tech, telecom, agriculture, insurance, cybersecurity, and retail.

Best Industries for Data Science: Table of Contents

  1. Data Science in Healthcare
  2. Data Science in the Oil and Gas Industry
  3. Data Science in Big Tech Companies
  4. Data Science in Telecom
  5. Data Science in Agriculture
  6. Data Science in the Insurance Industry
  7. Data Science in Cybersecurity
  8. Data Science in Retail
  9. Best Industries for Data Science: Next Steps

Data Science in Healthcare

Data is an integral part of all areas of medicine. In fact, the healthcare sector accounts for over 30% of the global data volume. Just imagine the amount and variety of information available from clinical trials, electronic health records, disease registries, etc.

This creates many opportunities. Data science applications in healthcare are numerous – from predictive testing to creating wearables and detecting anomalies in patient data.

Do data science jobs in healthcare sound exciting?

You can learn how to acquire such employment in our detailed guide on How to Become a Data Scientist in Healthcare.

Now, let’s look at the next sector.

Data Science in the Oil and Gas Industry

With a staggering profit of nearly /$3 billion daily, the oil and gas sector is one of the world’s most significant—making it the perfect arena for data scientists.

Using insights from big data, data scientists can help optimize operations, reduce errors, and bring maintenance costs down. But this involves working with certain sources and types of information you won’t encounter elsewhere, such as drilling data and well logs.

So, to become a data scientist in the oil and gas industry, you must have a good grasp of the basic operations in this sector. You’ll also need a specific set of technical skills and knowledge to run experiments and simulations.

Data Science in Big Tech Companies

The Big Five tech giants (FAANG) are arguably the top companies for a data scientist.

Amazon, Netflix, Google, Meta, and Apple use data science to improve user experience, build personalized recommendation systems, create innovative solutions, etc.

Becoming a data scientist in a Big Tech firm requires a lot of hard work, but it’s well worth it in the end. There’s a reason why they are considered the top data scientist companies. Not only do they offer big salaries, but they’re also at the forefront of innovation.

Data Science in Telecom

The telecommunication industry generates massive amounts of data types every minute, including customer information, call details, network data. As a data scientist in this sector, you must be able to manage all of it.

For that purpose, you’ll need a firm grasp of the different areas of data science and solid domain knowledge, which slightly differs depending on the company you work for—e.g., satellite, telephone, internet service provider.

Still, the basic skills and knowledge you need to become a data scientist in the telecom industry fall within the same scope.

Data Science in Agriculture

Agriculture may not be the most obvious choice for a data science job, but there are many applications for such employment. A company, for example, could hire a data scientist to analyze soil, yield, and weather data to help improve production.

A data scientist’s role in agriculture companies could also involve developing data pipelines for automation and scalability, building machine learning models to predict weather conditions and plant diseases, etc. Again, domain knowledge and analytics skills are essential to becoming a data scientist in agriculture.

Now, let’s continue with a few more typical industries looking for data science specialists.

Data Science in the Insurance Industry

Insurance companies are just one example of the application of data science in finance.

Data scientists working in this sector must be familiar with the basic terminology and recent developments, which will aid them when performing tasks like risk modeling, customer segmentation, lifetime value prediction, etc.

This aligns with the traditional perception of data science specialists, like in the tech sector.

Data Science in Cybersecurity

Cybersecurity deals with preventing global cybercrime. Data scientists can aid those efforts by creating models to understand the patterns of malicious activities and eventually predict them.

One thing is for sure – if you follow this career path, you won’t be left without your bread and butter. The demand for data scientists in this field is huge. The number of attacks and breaches has increased by 15% from 2020 to 2021 – and they’re getting harder to detect.

To catch up with cybercriminals, employers in the cybersecurity sector are looking to hire more data scientists. If you become a data scientist in cybersecurity, you won’t be disappointed.

Data Science in Retail

The role of a data scientist in retail can give companies a competitive advantage—helping to understand, for example, customers’ needs and wants.

Retailers all over the world are hiring data scientists to improve customer service, optimize production, and reduce losses. To succeed in this field, you need business knowledge and technical skills, such as how to build customer churn prediction models.

How big is the data science industry?
The data science industry is getting bigger and continues to grow. In 2012, the Harvard Business Review called data science “the sexiest job of the 21st century.” Ten years later, that still holds true. From 2013 to 2018, job postings increased by 256. And the employment of data science experts is expected to grow by another 27.9% from 2016 to 2026 – much faster than the average growth rate. This increase is also reflected in the salaries. As of 2022, the average annual pay of data scientists in the US is \$122,480.

 

Which companies have good product data science roles?
One of the roles a data scientist might perform is testing and optimizing products. And what better place to do that than the Big Five? These companies allow you to work at the heart of innovation with big data sets a data scientist could only dream of. (Not to mention the compensation.) Note the following list of the Big Five firms with their average data scientist salary. These are some of the best-paid data science roles: • Google: \$206,752 • Meta: \$194,507 • Apple: \$173,863 • Netflix: \$164,977 • Amazon: \$162,577

 

Best Industries for Data Science: Next Steps

Did you choose one of these industries for your data science career?

Great! It’s time to start learning with 365 Data Science.

Begin from the basics and work your way up to your dream job with our Data Scientist Career Track. Or, if you’re further along your career path, check out the advanced specialization options we offer, such as Fashion Analytics with Tableau or Python for Finance.

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Aleksandra Yosifova

Blog author at 365 Data Science

Aleksandra is a Copywriter and Editor at 365 Data Science. She holds a bachelor’s degree in Psychology and is currently pursuing a Master’s in Cognitive Science. Thanks to her background in both research and writing, she learned how to deliver complex ideas in simple terms. She believes that knowledge empowers people and science should be accessible to all. Her passion for science communication brought her to 365 Data Science.

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