5 answers
Max
Student
Mossman, QLD
2
Questions
Updated
795 views
Computer science or mathematics + statistics?
I'm a Year 11 student in Australia trying to decide between:
1. Data Science / Computer Science
More focused on programming, data, AI/ML and computing.
2. Bachelor of Science — Mathematics & Statistics + Applied Computing
Stronger maths/statistics foundation while still getting significant computing and programming.
For people working in these fields, which pathway would you recommend and why? How much does the degree title matter to employers compared with the actual subjects and skills you have?
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5 answers
Andrew Au
Professor of Mathematics & Statistics, Retired
258
Answers
Updated
Andrew’s Answer
The foundation of data science is mathematics and statistics.
Hence, a bachelor’s degree of science in mathematics and statistics + applied computing would be a better option. With a strong foundation on the basics, you can always work your way into the ever evolving areas of data science, AI/ML, and computing (even quantum computing in the future).
Employers will always be looking for adaptability and flexibility in employees. With strong foundational skills, you will always be trainable to meet the challenge of new and enveloping areas.
Hence, a bachelor’s degree of science in mathematics and statistics + applied computing would be a better option. With a strong foundation on the basics, you can always work your way into the ever evolving areas of data science, AI/ML, and computing (even quantum computing in the future).
Employers will always be looking for adaptability and flexibility in employees. With strong foundational skills, you will always be trainable to meet the challenge of new and enveloping areas.
Thanks Andrew,
hat's exactly what I was thinking, with a mathematics + statistics degree I would be able to get into jobs like data science while also having the flexibility to choose different options, whereas with a data science degree I would be locked into that. I think I will be going with that degree however as I still have a year and a half to go nothing is locked in yet
Max
Rebecca Tang
Banking
2741
Answers
Hong Kong
Updated
Rebecca’s Answer
Thank you for your question. The most important is what careers you have interest.
Below are my suggestions :
1. For Data Science / Computer Science, you can consider to careers like Machine Learning/LLM Engineer, LLM Trainer, Web Developer, Apps Developer, etc.
For Mathematics & Statistics + Applied Computing, you can consider careers like Data Analyst, Business Intelligent Analyst, Risk Manager, Financial Model Developer, etc.
2. Find out more on the careers and determine what you have interest
3. Attend the information session hosts by the department of colleges. Speak to the professors if you can on the future career path
4. Seek guidance from your mentor, school career counsellor, etc.
5. Shortlist 1-2 careers you would like to pursue
6. Find out the entry criteria of relevant subjects in college
Hope this helps! Good Luck!
May Almighty God bless you!
Below are my suggestions :
1. For Data Science / Computer Science, you can consider to careers like Machine Learning/LLM Engineer, LLM Trainer, Web Developer, Apps Developer, etc.
For Mathematics & Statistics + Applied Computing, you can consider careers like Data Analyst, Business Intelligent Analyst, Risk Manager, Financial Model Developer, etc.
2. Find out more on the careers and determine what you have interest
3. Attend the information session hosts by the department of colleges. Speak to the professors if you can on the future career path
4. Seek guidance from your mentor, school career counsellor, etc.
5. Shortlist 1-2 careers you would like to pursue
6. Find out the entry criteria of relevant subjects in college
Hope this helps! Good Luck!
May Almighty God bless you!
Sachin Munshi
Adjunct Online Math Instructor
7
Answers
Albany, New York
Updated
Sachin’s Answer
Hello Max,
I think it's great that you're already considering what your academic and professional goals are as you prepare for entering college. The two options you brought up are really good ones, particularly with respect to today's technological advances.
My suggestion would be to go with the second option, i.e., Bachelor of Science - Mathematics & Statistics + Applied Computing, to begin with. This would lay a nice foundation for your interest in computer and data science. If this goes well for you and you would like to pursue further ahead, then you may start working towards the first option of Data Science/Computer Science. The names of the degrees, of course, aren't as important as the courses required and skills learned and maintained in order for you to achieve one or both those degrees, as you so choose.
So, start with the math to get to the science! I wish you the very best of luck. :)
I think it's great that you're already considering what your academic and professional goals are as you prepare for entering college. The two options you brought up are really good ones, particularly with respect to today's technological advances.
My suggestion would be to go with the second option, i.e., Bachelor of Science - Mathematics & Statistics + Applied Computing, to begin with. This would lay a nice foundation for your interest in computer and data science. If this goes well for you and you would like to pursue further ahead, then you may start working towards the first option of Data Science/Computer Science. The names of the degrees, of course, aren't as important as the courses required and skills learned and maintained in order for you to achieve one or both those degrees, as you so choose.
So, start with the math to get to the science! I wish you the very best of luck. :)
Jean Noel Sanchez
Developer/Data Analyst
109
Answers
New York, New York
Updated
Jean Noel’s Answer
Hi - Degree titles matter far less to employers than your coursework, project portfolio, and practical skills.
Tech and data hiring managers look primarily at whether you can write clean code, pass technical interviews, and demonstrate foundational logic. An HR filter might flag "STEM degree required," but both Computer Science and Bachelor of Science (Math & Stats) clear that threshold instantly.
Pathway Breakdown
Option 1: Data Science / Computer Science
• Focus: Algorithms, software engineering, systems design, object-oriented programming, and applied AI/ML pipelines.
• Pros: Gives you a strong software engineering safety net. If AI/ML roles prove competitive, you can seamlessly shift into software engineering, full-stack development, or platform engineering. You will learn production-level coding, Git, and software architecture early.
• Cons: You may miss deeper theoretical statistics (e.g., advanced measure theory, experimental design theory) that can prove valuable for high-level ML research.
Option 2: Science (Math & Stats + Applied Computing)
• Focus: Linear algebra, probability theory, statistical inference, multivariate calculus, plus fundamental programming.
• Pros: Teaches you how algorithms work under the hood rather than just how to call a pre-built library. This path offers a clear advantage for roles in specialized AI research, quantitative finance/trading, and advanced statistical modeling.
• Cons: You may get less exposure to production software development practices—such as building large-scale web applications, cloud infrastructure, or complex software architectures—unless you actively seek them out via electives or personal projects.
Which Pathway to Choose?
1. Choose Computer Science / Data Science if:
o You want maximum career flexibility across mainstream tech roles (software engineer, data engineer, systems developer, machine learning engineer).
o You prefer building products, writing production code, and working with software tools over mathematical proofs.
2. Choose Math & Stats + Applied Computing if:
o You excel at mathematical logic and want a deep theoretical foundation for machine learning, research, or quantitative finance.
o You are comfortable learning higher-level software development practices on your own (or through your computing units) while mastering stats at university.
Advice for Year 11
As a Year 11 student in Australia, focus on building strong foundations before selecting a university preference:
1. Prioritise Methods or Specialist Mathematics: Keep higher-level maths options open in Year 11/12 (e.g., Mathematical Methods or Specialist Mathematics, depending on your state curriculum). Strong high school math unlocks both pathways and reduces the need for university bridging courses.
2. Look for Double Degrees or Elective Space: Many Australian universities allow double majors or double degrees (e.g., Computer Science / Science with a Mathematics major). You often do not have to choose strictly between the two.
3. Start Coding Early: Spend time outside of school building small projects in Python or SQL. Doing so will help clarify whether you enjoy building software architecture (favoring CS) or analyzing patterns and data models (favoring Stats).
Tech and data hiring managers look primarily at whether you can write clean code, pass technical interviews, and demonstrate foundational logic. An HR filter might flag "STEM degree required," but both Computer Science and Bachelor of Science (Math & Stats) clear that threshold instantly.
Pathway Breakdown
Option 1: Data Science / Computer Science
• Focus: Algorithms, software engineering, systems design, object-oriented programming, and applied AI/ML pipelines.
• Pros: Gives you a strong software engineering safety net. If AI/ML roles prove competitive, you can seamlessly shift into software engineering, full-stack development, or platform engineering. You will learn production-level coding, Git, and software architecture early.
• Cons: You may miss deeper theoretical statistics (e.g., advanced measure theory, experimental design theory) that can prove valuable for high-level ML research.
Option 2: Science (Math & Stats + Applied Computing)
• Focus: Linear algebra, probability theory, statistical inference, multivariate calculus, plus fundamental programming.
• Pros: Teaches you how algorithms work under the hood rather than just how to call a pre-built library. This path offers a clear advantage for roles in specialized AI research, quantitative finance/trading, and advanced statistical modeling.
• Cons: You may get less exposure to production software development practices—such as building large-scale web applications, cloud infrastructure, or complex software architectures—unless you actively seek them out via electives or personal projects.
Which Pathway to Choose?
1. Choose Computer Science / Data Science if:
o You want maximum career flexibility across mainstream tech roles (software engineer, data engineer, systems developer, machine learning engineer).
o You prefer building products, writing production code, and working with software tools over mathematical proofs.
2. Choose Math & Stats + Applied Computing if:
o You excel at mathematical logic and want a deep theoretical foundation for machine learning, research, or quantitative finance.
o You are comfortable learning higher-level software development practices on your own (or through your computing units) while mastering stats at university.
Advice for Year 11
As a Year 11 student in Australia, focus on building strong foundations before selecting a university preference:
1. Prioritise Methods or Specialist Mathematics: Keep higher-level maths options open in Year 11/12 (e.g., Mathematical Methods or Specialist Mathematics, depending on your state curriculum). Strong high school math unlocks both pathways and reduces the need for university bridging courses.
2. Look for Double Degrees or Elective Space: Many Australian universities allow double majors or double degrees (e.g., Computer Science / Science with a Mathematics major). You often do not have to choose strictly between the two.
3. Start Coding Early: Spend time outside of school building small projects in Python or SQL. Doing so will help clarify whether you enjoy building software architecture (favoring CS) or analyzing patterns and data models (favoring Stats).
Eria Othieno Pinyi
Software Engineer & Architect
9
Answers
Davenport, Iowa
Updated
Eria Othieno’s Answer
Hello Max,
Both options are strong, and the subjects you study and skills you gain are more important than the degree title. If you're most interested in software development and programming, I suggest choosing Computer Science. If you like math and want to explore AI, data science, statistics, and quantitative careers, consider Mathematics & Statistics + Applied Computing, as long as it covers programming, algorithms, and data structures.
Employers might look at the degree title initially, but they care more about your technical skills, projects, internships, and relevant coursework. After your first few jobs, the title matters even less.
So, it's better to choose based on the subjects in the degree rather than its name.
Good luck, Max!
Both options are strong, and the subjects you study and skills you gain are more important than the degree title. If you're most interested in software development and programming, I suggest choosing Computer Science. If you like math and want to explore AI, data science, statistics, and quantitative careers, consider Mathematics & Statistics + Applied Computing, as long as it covers programming, algorithms, and data structures.
Employers might look at the degree title initially, but they care more about your technical skills, projects, internships, and relevant coursework. After your first few jobs, the title matters even less.
So, it's better to choose based on the subjects in the degree rather than its name.
Good luck, Max!