Problem-Solving: Risk management is a complex field, and the data sets are never the same. While this makes each job unique, it requires a high degree of problem-solving. Using external knowledge to extract relevant insights is a critical skill.
Computing Knowledge: Actuaries must have strong computer skills, both to understand how software processes data and to share results across different platforms.
Mathematics and Statistics: To effectively analyze data, an actuary must be familiar with statistics, probability, calculus, and accounting, as well as recognizing and interpreting trends within a data set.

Actuaries' Essential Skills

Necessary Skills for Data Scientists
Data scientists must have a set of specialized skills.

Critical Thinking: Thinking critically about a problem helps data scientists formulate hypotheses and narrow down data sets to offer accurate insights.
Programming: While generalized computer skills still form part of a data scientist’s qualifications, they need to know far more about computers than other professions. Learning the syntax and forms for languages such as R, Python, and C# offers data scientists the ability to automate data processing. With the sheer size of the data pools these scientists deal with, programming is a core skill.
Mathematics: Data scientists should have a strong background in linear algebra, calculus, and statistics. Many companies require data scientists to have an advanced degree in mathematics or a related field.

Essential skills for a data scientist

Comparing Actuary vs. Data Scientist
Actuaries and data scientists differ in several ways. A data scientist’s scope is often broader than that of an actuary, while actuaries are more familiar with the nuances of statistical probability than data scientists. Data scientists often develop programs to help them process data, while actuaries use existing programs to help them determine risk. Finally, actuaries deal primarily with financial risk, while data science can be applied to any field that relies on large amounts of data.

Quality education is essential whether a student is interested in a career in data or actuarial science. At Maryville University, students can choose between two degree options to prepare for these paths. The Online Bachelor of Science in Mathematics program teaches students fundamentals including calculus and number theory, and offers a minor in data science with courses in coding and machine learning.  The Online Bachelor of Science in Data Science focuses on mathematical principles like statistics and probability, as well as math modeling and machine learning skills, and offers a concentration in actuarial science that provides students with the skills they need for a rewarding career as an actuary.

Maryville U: Comparing Actuary vs Data Scientist

https://online.maryville.edu/blog/actuary-vs-data-scientist/

University of Michigan - Ann Arbor

Study of financial risk and uncertainty. Combines elements of Business, Data Science, Statistics, and CS to help quantify financial risk. Actuaries are mostly hired into the Financial or Insurance industries to model various economic uncertianties.

Actuarial Mathematics

https://online.maryville.edu/blog/actuary-vs-data-scientist/
Actuary:
An actuary’s job is based on the premise that, given enough data, the right calculations will yield actionable insights that businesses can take to mitigate risk.

Data Scientist:
Like actuaries, data scientists spend their time analyzing data and making statistical predictions. However, unlike actuaries, who work primarily in insurance and deal chiefly with numbers, data scientists use a wide range of data to make predictions about a broader range of topics.

Actuary vs Data Scientist

Actuary and Data Science career differences article

Actuarial Mathematics Edition: 2nd Author(s): Bowers, Newton L.; Gerber, Hans U.; Hickman, James C.; Jones, Donald A.; Nesbitt, Cecil J.
UM resources: https://lsa.umich.edu/math/undergraduates/major-and-minor-programs/actuarial-mathematics.html

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