How do I choose between being an Actuary or Data Scientist?

Share it

Reditt had an interesting conversation going eight months ago about this very topic, how to choose between being an actuary or data scientist? Unsurprisingly, the actuaries thought their career path was a better choice and the data scientists argued just as strongly for their choice. The interesting responses were the ones who had done both so had a better picture of what each career choice involved. Most of the transitions were from actuarial science to data science but there was one person who had gone the other direction. Here are their main reasons for the choices they made between being an actuary or data scientist.

Being an Actuary

  1. Like the idea of working in insurance – a stable, lucrative industry. Great benefits.
  2. High growth job market where your skills will be in demand. Unemployment is almost unheard of.
  3. Like the idea of taking exams that the company will pay for, even pay you for the time you spend studying, versus paying for your own Master’s degree
  4. .Like the accreditation and credentials that are set up for the career path. Easily quantifiable and as a result easy to argue for compensation increases and promotions as each threshold is achieved.
  5. Once you have finished your exams and attained an ASA or FSA accreditation, being an actuary is viewed as an “easier”, less stressful work life with regular hours.
  6. Compensation is consistent across the country. You don’t take a pay cut for working in lower cost of living areas.
  7. Enjoy working in Excel and “excel” at it, and don’t have any desire to learn other programming languages.
  8. You like structure and don’t chafe at working within a regulatory environment.

Being a Data Scientist

  1. Get jazzed at the idea of working in different industries, or not being limited to one.
  2. High growth job market where your skills are in demand, but matching what you want to do with how the company defines their opening is sometimes challenging.
  3. Have a Master’s or PhD in a quantitative discipline. Some extremely technical bachelor’s can succeed but they tend to be funneled into data analyst jobs versus data scientist.
  4. On-the-job experience makes you extremely marketable and compensation is negotiable based on the tightness of the supply of data scientists and the variety of skills you have.
  5. You need to be a lifelong learner. New applications, new sources of data, new software are the standard not the exception. Keeping up can be stressful, both your own education and bringing new things into your organization.
  6. Data Science typically has higher compensation early in their career but it does plateau. This may change as data science groups increase in size and management becomes more important.
  7. You are primarily a statistician but doing your own programming feels like a plus not a negative. You can pick up programming languages easily.
  8. You love being innovative and defining the business problem as well as solving it.

The actuarial science career path is feeling the pressure of big data and open source software. The actuarial accreditation societies are trying to add this expertise to actuaries through the exam process. As recruiters in the actuarial and data science area we see actuaries including data science in their job most effectively when they are part of a larger organization that has both an actuarial group and a data science group. AnalyticsIndiaMag.com reports that actuaries choosing to interface or do projects with the data scientists is the most effective way to build skills that will be needed to be a good actuary…not quite yet, but the career is heading in that direction.

Data Scientists targeting the actuarial career have a clear cut path, pass exams.  You will have to do them on your own time and with your own dollar, but the credentials they give you will smooth your entry into this career.

Rory Hauser, Actuarial Science Recruiting Practice Lead as Smith Hanley, says, “It is easier for an actuary to learn data science than a data scientist to learn the insurance industry.” Perceptive, career-driven actuaries should jump at the opportunity to expand their skill set within their own organization.  Data Scientists looking for a more structured environment can transition to being an actuary through the actuarial society’s accreditation process.

Interested in discussing your career or hiring an analytical specialist? Contact the Smith Hanley Associates’ Actuarial and Data Science Recruiting Team:
Rory Hauser, rhauser@smithhanley.com
Nancy Darian, ndarian@smithhanley.com
Paul Chatlos, pchatlos@smithhanley.com


Share it

Related Posts

artificial intelligence

How AI Will Impact Actuaries

Artificial intelligence (AI) has been growing in usage for several years now through innovative applications in numerous fields. The actuarial profession is no exception to

Read More »