You are a math whiz, and you enjoy solving problems, but you love the practical application of your skills not the theoretical math career an academic PhD offers. As you consider your career options before or during your pursuit of your bachelor’s degree, two choices rise to the top. Do you want to be an actuary or data scientist? Here is a breakdown of differences between the two that might help you make your decision.
Highly Respected Profession
Winner: Actuary
Because the Chief Actuary of most organizations is a critical role on the executive team the value of actuaries seems to be perceived higher across the board
Second Place: Data Scientist
Everyone knows the data scientist is very smart and can provide great bottom line impact but since few in the organization understand what they do, it can be perceived as a back office role.
Sophisticated Analytics
Winner: Data Scientist
There’s a reason why the data scientist role is the number one open position in the U.S., technological advances and the availability of unstructured, real-time data allows the gifted data scientist to do interesting and valuable work for their businesses. Keeping up with the latest application is part of the job.
Second Place: Actuary
Because the actuarial certification process is more structured adding exams to reflect new statistical techniques and new opportunities for real data versus estimation science change has been slow to occur.
Work/Life Balance – First Seven Years of Career
Winner: Data Scientist
The junior data scientist will spend time interfacing with IT and marketing as well as doing data cleaning, analysis and data visualization. In larger organizations their supporting role early in their career isn’t as taxing as it becomes later on when they have bottom line impact responsibility.
Second Place: Actuary
Finding time to study for 7 exams before obtaining your FSA or FCAS and working your job at the same time can mean very little me time.
Work/Life Balance – After First Seven Years
Winner – Actuary
Once you have received your FSA/FCAS you are in a career with virtually 0% unemployment. The value of an actuary to an organization means they want you happy. You will have a staff to do the hands-on technical work and a very regular work schedule.
Second Place – Data Scientist
As the Data Scientist moves up in their career, their hands-on value to the organization only increases. You will not only be managing staff and responsible for impacting profit, you will still be hands-on as technology changes so rapidly, you have to be knowledgeable about the latest and greatest. Time management will be an important skill to master.
Versatility
Winner – Data Scientist
This was a close call as both careers have a high level of versatility. Data Science edged out actuarial science because they don’t have the restriction of accreditation and data science can be applied in almost every industry or anyplace there is some accumulation of data.
Second Place – Actuary
Because of the accreditation required there are some limits to this career but health, retirement, banking, government, investments and, of course, insurance are all industries where actuaries shine. There is also a variety of risk related roles that an actuary can pursue.
Meaningful, Challenging and Rewarding Work
Winner – Actuary
The ability to price risk is critical for our economy and our society. The recommendations and decision you make as an actuary will have widespread financial impact on many lives.
Second Place – Data Scientist
Your expertise and day-to-day problem solving will be challenging and rewarding but predominantly for the company you are working for.
Compensation
Winner – Actuary
Both careers are financially rewarding but anytime there is an accreditation process the compensation structure is more standardized and often rewards those who achieve the highest qualifications. Working at larger organizations can offer greater benefits beyond the base salary and bonus.
Second Place – Data Scientist
This was a close call as data science is a less structured, but very well compensated career path for those who can prove their value. There is also the opportunity for the gifted data scientist to be more entrepreneurial and start their own business.
