Actuarial science and data science both offer exciting career paths, but which one is right for you? Our expert coaches, Jon Lai and Larry Saw, break down the key differences in skill sets, career paths, and earning potential to help you make an informed decision about your future.
From Google’s search algorithms to Netflix’s recommendation system, from urban planning to financial trading, data-driven decision-making is all the rage. In this data-driven era, two fields are emerging as prominent players: actuarial science and data science.
To break down the differences between actuarial science and data science, we consulted our expert coaches, Jon Lai and Larry Saw. Together, they explored the factors influencing why students are choosing one field over another for their career.
Coaching Actuaries is, obviously, focused on actuarial science; however, we’ve endeavored to remain objective and informative in this article to help you make the right decision!
How are actuarial science and data science different?
While they share a common foundation in analyzing data, these fields differ significantly in their focus and skill requirements.
"Actuaries need to effectively communicate their results within the context of business problems,” says Coach Larry, “while data scientists focus on data analysis." A proficiency in soft skills allows actuaries to play a pivotal role shaping the future of their organizations.
In comparison, data scientists extract insights from data through advanced analytics techniques. They apply technical skills in programming, statistical analysis, machine learning, and data visualization.
Coach Jon adds, "Actuarial science is primarily about managing financial risk [while] data science is focused on understanding data, with less emphasis on the specific field of application."
To illustrate this difference, Jon presents a food analogy: "If we consider cooking as data science, then actuarial science is akin to the art of French cuisine."
Let's compare key aspects that differentiate actuarial science and data science:
Why choose actuarial science or data science?
According to our coaches, the right choice depends on your personality and career aspirations.
Explains Coach Larry, "If you like to talk to management and decision-makers, choose actuarial science. If you want to focus on analyzing data, choose data science."
There's also the question of career path to consider. "The path to becoming an actuary is a well-worn one," says Coach Jon, "with a distinct accreditation to recognize your qualification. But there is no clear 'career structure' with data science."
Nevertheless, data science offers many opportunities. "As a data scientist,” Jon adds, “you can apply your knowledge to a vast spectrum of fields, which implies there are numerous opportunities that won't require too much rigor or challenge."
In comparison, says Coach Jon, "the pursuit of an actuarial career is going to be a challenge to most if not all."
Why is data science so hot?
Data science is experiencing tremendous growth for a variety of reasons, as Coach Jon highlights: “Technology is very much tied to data analysis and tech is usually something that gets people hyped.”
In addition, the omnipresence of the internet and the abundance of Big Data in our lives have further contributed to this trend. Companies in control of such data are eager to analyze it for a multitude of motivations.
“The rise of Big Data and the need to analyze millions or billions of rows of data is driving the demand for data science,” explains Coach Larry. Coach Jon agrees, "The value placed on data is increasing in just about every facet of life.”
In addition, says Larry, “Improvements in technology make it easy for anyone to access and learn about data science.” This quality makes data science uniquely accessible, while actuarial science requires following an established pathway by the Society of Actuaries (SOA) and other governing bodies.
However, actuarial science is also uniquely accessible. Even if you attend a non-top-tier institution and pursue a major unrelated to math or business, you can establish a successful career as an actuary. Overcoming the field’s challenging exams gives you credibility and expertise.
Which field brings a higher salary?
According to the U.S. Bureau of Labor Statistics (BLS), both professions offer attractive earning potential. Data scientists earn an average annual salary of $100,910, while actuaries earn slightly higher at $105,900.
According to Be an Actuary, a resource created by the SOA, experienced fellows in the actuarial field might earn a substantial annual income ranging from $150,000 to $250,000, with many actuaries surpassing this range.
Be an Actuary emphasizes compensation can vary significantly based on years of experience, industry, geographic region, and job responsibilities: “For example, an actuary with a fellowship designation working as a financial manager in the banking industry could earn a higher salary than [one] working in the health insurance industry.”
Career outlook is also important to consider. Through 2031, data science has a projected job growth rate of 36%. This indicates a strong demand for skilled data scientists. Actuarial science also has positive job prospects, with a growth rate of 21% during the same period, particularly in the insurance and financial sectors.
Considering salary and job outlook, both data science and actuarial science offer lucrative opportunities. If a higher average salary is a priority, actuarial science may be more appealing. However, data science is a strong contender!
How is the actuarial science field responding?
Actuarial science governing bodies aren’t sitting still in response to the momentum around data science.
In fact, says Coach Larry, “The SOA is designing programs for data science and expanding the exams to cover data science topics. This is evident with the recent introduction of Exam SRM (Statistics for Risk Modeling), Exam PA (Predictive Analytics), and Assessment ATPA (Advanced Topics in Predictive Analytics).”
Coach Jon adds, “There has been a shift to emphasize data science more and earlier in the actuarial accreditation process.” Jon says this reflects the fact that “more actuaries are leveraging data science knowledge and tools in their work.”
In addition, the SOA is introducing a data science and predictive analytics certificate that requires fewer exams than the Associate of the Society of Actuaries (ASA)/Fellow of the Society of Actuaries (FSA) track, which Larry describes as “enticing.”
In the future, instead of pondering whether to choose data science or actuarial science, you might ask, "Why not both?" Actuarial science roles are increasingly offering a multitude of data science opportunities!
Questions?
Our coaches are here to help you sort through whether actuarial science or data science is right for you! Email [email protected] or post on our discussion forums with your career questions.