Will Data Science Replace Actuaries? (We Find Out)

Data science is a vast field . It packs many different fields within its domain and hence has a wide range of applications, consequently making data scientist “The Sexiest Job of the 21st Century”. 

According to Google Trends, the interest in the said field has increased by around 4 times within the past 4 to 5 years.

Amongst all other professions that data science has endangered with its evolving nature lately, actuaries have also started to feel threatened. The fact that actuaries have an overlapping skillset to data scientists and much narrower scope, there’s a lot of confusion going around if both fields will eventually overlap.

Actuaries possess a high-level skillset when it comes to mathematics and statistics. However, data scientists have programming skills, on top of mathematics and statistics skills, which gives them the upper hand. Moreover, programming lets them automate tasks using predictive models, which is far beyond the scope of actuaries.

However, many other factors need to be considered if we need to decide the future of actuaries. In this article, we will analyze if data science can replace actuaries and some key differences between both professions.

Brief Definitions

Now before we dig deeper into the details, you must have an overview of both these fields. It will help you fully understand what actuaries and data science are all about.

Data Science is a multi-disciplinary field that combines programming, mathematics and statistics, and big data. It’s responsible for managing all kinds of data to make it useful for businesses, and it’s used to design automated solutions to existing problems using it.

However, it’s quite hard to find professionals who specialize in all the skills mentioned above – that is partially the reason why data scientists are a huge asset to any business. They’re one-man-army who possess the ability to tackle complex problems all by themselves. From collecting the raw data using multiple sources to designing solutions based on it, they manage everything.

Actuaries are the study of analyzing risks, probabilities, and certainty when it comes to financial problems. They are the key professionals in any financial domain, such as insurance companies. They use their mathematical and statistical concepts to assess certain risky situations and test potential hypotheses based on economic events and relevant data.

Actuaries are actually the masterminds behind huge insurance organizations responsible for devising all the insurance policies. They use their skills to achieve the best profit-to-risk ratio. 

Even though a bachelor’s degree is enough to become an actuary, the US BLS states it takes around 4 to 7 years for actuaries to earn an associate-level certification.

Will Data Science Replace Actuaries?

Will Data Science Replace Actuaries?

Data science and actuaries overlap a lot. Rigorous mathematical and statistical studies define Their foundation. Although data scientists go through pretty similar phases as actuaries when coming up with solutions to complex problems, there’s still a huge gap in the roles being played by the two professions.

While data science covers most of the skills required for actuaries, it won’t be anytime soon that it’s enough for the financial industry’s specific needs, if ever. Both fields have their importance, and even though actuaries have a minimal scope, they are not easily replaceable merely by having enough statistical skills.

Certain training and certifications are required to be competent for an actuary’s job that is not possessed by data scientists, no matter how much they’re qualified. 

Now, let’s jump on to both data scientists and actuaries’ job responsibilities to see how they’re different.

Data Scientists Vs. Actuaries

In this section, I’ll be comparing the job roles of both data scientists and actuaries in contrast so that we can easily discern the differences. You’ll also be able to figure out how their professional lives go about.

Data Scientists Job Responsibilities

Data scientists are the people who can make use of any form of data to ever exist to their advantage. Their sole purpose is to achieve value using data in all sorts of problems. They have a pivotal role to play in every industry nowadays since data gives a lot of insight into your customers. If it weren’t for data scientists , most of the data would be going to waste.

Data scientists are also responsible for solving complex business problems using the available business data in addition to studying the data to extract different customer and market trends. 

Since they’re skilled in ML algorithms and their implementation, not only do they solve these problems, but they also automate them to ensure that there’s minimal human interaction needed in trivial tasks such as data extraction and ETL.

Hence, to summarize, here are some crucial skills required for a data scientist.

  • Machine learning algorithms.
  • Programming/automating solutions.
  • Critical thinking.
  • Business Knowledge.
  • Big data.
  • Strong grip on mathematical concepts.

Actuaries Job Responsibilities

We’ve already established the fact that the basis of actuaries relies upon risk management. The professionals collect the data related to the instance and use it to find any patterns that could help in mining insights resulting in the calculation of mitigating risks. These are computationally expensive tasks since tons of data need to be explored before anything useful comes in hand.

Even though actuaries’ roots go back to the 17th century, and back then, they didn’t rely upon any automated ways to process data; the field has evolved a lot since then. Nowadays, actuaries use heavy statistical software for processing and don’t manually go through hundreds of pages to find the right data and patterns from it. Here are some essential skills required in commercial jobs.

  • Sound knowledge of financial risk management.
  • Designing and testing insurance policies.
  • Statistical Problem-Solving.
  • Basic Computer Knowledge.

The Differences

Now that it’s clear how the job responsibilities differ in both areas. Let’s explore some head-to-head differences between the two fields, which keep data scientists from being a threat to actuaries. I’m going to drop some bullets to make it easy for you to point out the differences.


The domain is the foremost difference that marks the boundaries of the two fields. I’ve been stressing over this point from the very start for a reason. Actuaries’ goals are strictly limited to financial companies, but there are no bounds for data science. Not that they’re experts of all domains ever to exist, but they have enough business knowledge that they know integrating data science knowledge with specific business-related problems.

For example, an actuary might be asked to calculate the renewal rate for a certain insurance policy based on some specific scenario. This is a pretty routine task for an actuary, but not something data scientists could entertain. On the other hand, a data scientist could be asked to analyze the potential areas for opening a new branch of a clothing brand. From collecting the business data for this use case to selecting the best location, they manage everything.


The education and the training matter a lot and develop the sense in an individual to tackle real-life problems. Actuarial sciences provide very specific training such as FSA, ASA, CERA – which lets them have an extensive knowledge of all statistical concepts required in their domain.

On the contrary, data scientists don’t receive any formal training to test their statistical skills, even though they have a top-notch mathematical background and are second to none. 

In conclusion, data scientists fail to handle tasks easily handled by actuaries despite their skills.


There is a huge gap between actuaries and data scientists when it comes to tools. While the former are more habitual of using statistical software such as VBA, SAS, SQL, the latter has more of a programming approach; using programming languages such as R and Python and using on SQL databases Hadoop and Apache Spark.

Will Data Science Replace Actuaries?

The Future of Actuaries

Data science might be a threat to some actuarial roles that require minimal human interaction and don’t involve high-level financial knowledge. It’s safe to say for the foreseeable future that actuaries are far from the danger-zone being created by the advancement of data science.

Most of the complex problems still require a lot of human interaction and specific domain knowledge. If anything, data science is a blessing in disguise for actuaries.

The transition from an Actuary to a Data Scientist

Learning programming languages and learning about automation should be among the top-most items in actuaries’ priority list. Not only would it make them more valuable to their organizations, but it’ll also let them stand tall against the data scientists looking to replace them.

If you want to pick up some data science skills and up your game from being an actuary to a data scientist, there are several free online courses you could explore. Check them out, Here.

Highly Recommended Next Post to Read:

Top 10 FREE Online Data Science Courses

Wrapping Up

With the swift advancement of data science, people fear that it’s not long before data scientists start replacing actuaries’ roles. Since both the fields are primarily based upon statistical studies, data scientists have the edge as they have programming skills as well. Moreover, data scientists are skilled in machine learning, which lets them automate certain mainstream processes. This wipes out a lot of human resources going to waste and saves companies considerable resources.

So, Will Data Science Replace Actuaries?

Throughout the article, we’ve seen that even though both jobs feel pretty similar from a broader perspective, a lot is going on in actuaries that cannot be entertained by data scientists yet. It’s not anytime soon that this gap will be filled, at least till data scientists don’t enlarge their skillset further. And actuaries can learn data science and have the edge on this!

So, except for a few minor changes here and there, including automating up to a certain extent, there’s no significant threat posed to actuaries by data science in the future.

Emidio Amadebai

As an IT Engineer, who is passionate about learning and sharing. I have worked and learned quite a bit from Data Engineers, Data Analysts, Business Analysts, and Key Decision Makers almost for the past 5 years. Interested in learning more about Data Science and How to leverage it for better decision-making in my business and hopefully help you do the same in yours.

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