Data Science vs. Actuarial Science: What’s the Difference?

Data Science

Actuarial Science

What Is It?

Data scientists rely on the usage of statistics, algorithms, and artificial intelligence to draw out useful insights for the purpose of analysing business operations, making a decision, and providing new advice and policy.

Advanced software is used in data science to process data and predict outcomes. Programming skills are therefore required from data scientists.

Actuaries, or actuarial scientists, utilises statistics and mathematics to foretell the financial risks of companies. This is done through data collection and the application of algorithms to develop an understanding of financial loss and return.

Actuaries often collaborate with accounting and finance departments. Their job is to help companies make decisions depending on the costs and profits. 

What Will You Study?

In this course you will be studying:

• Computing theories
• Data structure and management
• Programming for data analysis
• Research methods for technology
• Probability and statistical modeling

In this course you will be studying:

• Financial management
• Risk theories
• Regression analysis
• Principals of Programming
• Economics

What are Your Career Prospects?

• Software tool developer
• Analytics manager
• Data scientist
• Risk analyst
• Business intelligence developer
• Data analytics manager

• Actuarial reserving analyst
• Financial risk manager
• Financial planning advisor
• Bank executive
• Actuarial executive