Data scientist
Data scientists use statistics, programming and machine learning to find patterns in data and help organisations make decisions or build data-driven products.
What can you do with a data science degree?
Also called: Data analytics · Applied data science · Statistics and data science · Analytics
Updated How we use data
Quick answer
A data science degree teaches how to collect, clean, analyse and learn from data, combining statistics, programming and machine learning with knowledge of real-world problems. Graduates become data scientists, data analysts, statisticians, AI engineers and business analysts, and the skills are used in finance, healthcare, retail, technology, government and research.
Careers with a data science degree
Graduates are hired in almost every sector that collects data, including technology, finance, healthcare, retail, sport and government. Many start as data analysts or business analysts, then move into data scientist, machine learning or AI engineer roles. Those with strong statistics may become statisticians, and some take professional exams to become actuaries. Less obvious options include sports analytics, public health research, marketing analytics, fraud detection and data journalism. Employers often value a strong portfolio of projects as much as the degree itself.
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Data analyst
Data analysts collect, clean and study data to answer practical questions, such as which products sell best or where a service is failing.
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AI engineer
AI engineers, also called machine learning engineers, build and run systems that learn from data, such as recommendation tools, image recognition and applications based on large language models.
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Statistician
Statisticians collect, analyse and interpret data to answer questions and support decisions.
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Actuary
Actuaries use mathematics, statistics and financial theory to measure and manage risk, especially in insurance, pensions and investment.
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Business analyst
Business analysts help organisations improve the way they work.
Other roles graduates go into: Data engineer · Business intelligence analyst · Analytics engineer · Quantitative analyst · Marketing analyst · Fraud analyst
What you study and the skills you gain
Typical topics
- Programming for data science, usually in Python or R
- Probability and statistics
- Linear algebra and calculus
- Machine learning and artificial intelligence
- Databases and data management
- Data visualisation and communication
- Big data and cloud computing
- Data ethics, privacy and law
Skills you gain
- Writing code to clean, analyse and model data
- Choosing and applying statistical methods correctly
- Building and testing machine learning models
- Turning business or research questions into data problems
- Presenting results clearly with charts and plain language
- Handling data responsibly and ethically
How the degree differs around the world
Data science is a fairly new undergraduate subject, and many people still enter the field through a master's degree after studying mathematics, statistics, computer science, economics or a science. Bachelor's degrees usually take three years in the UK and much of Europe and four years in the United States, Canada and many Asian countries. Programmes run by mathematics departments tend to focus more on statistics, while those in computing or business schools are more applied, so compare modules carefully. Entry usually requires strong mathematics. Some programmes are accredited by computing or statistics bodies.
How do data science graduates do?
Earnings and employment by country
The OECD compares graduates by field of study. This subject falls under “Natural sciences, mathematics and statistics”. The first column compares the median earnings of tertiary-educated adults in this field with all tertiary-educated adults (100 = average).
| Country | Earnings index (all graduates = 100) | Employment rate, this field | Employment rate, all graduates |
|---|---|---|---|
| Costa Rica | 138 (2023) | 77.1% (2024) | 79.2% |
| Chile | 125 (2023) | 84.3% (2022) | 85.7% |
| United States | 117 (2023) | 84.8% (2017) | 84.3% |
| Norway | 111 (2023) | 86.5% (2024) | 89.3% |
| Denmark | 111 (2023) | 82.4% (2021) | 87.8% |
| Mexico | 109 (2023) | 78.3% (2024) | 81.5% |
| Slovenia | 108 (2020) | 93.2% (2024) | 90.8% |
| South Korea | 106 (2023) | — | — |
| Estonia | 105 (2023) | 89.2% (2024) | 89.2% |
| Canada | 105 (2020) | 80.1% (2021) | 80.4% |
| Switzerland | 104 (2023) | 87.7% (2024) | 89.5% |
| Finland | 103 (2022) | 88.4% (2024) | 88.8% |
| Australia | 103 (2020) | 86.2% (2024) | 88.4% |
| Austria | 102 (2023) | 82.6% (2024) | 86.4% |
| Portugal | 101 (2020) | 86.1% (2024) | 90.7% |
| Sweden | 100 (2023) | 85.3% (2024) | 89.6% |
| Germany | 97 (2020) | 86.1% (2024) | 88.7% |
| Romania | 96 (2023) | 92.4% (2024) | 91.5% |
| Luxembourg | 94 (2023) | 79.5% (2024) | 85.7% |
| Latvia | 93 (2023) | 89.3% (2024) | 87.7% |
| United Kingdom | 92 (2020) | 83.2% (2021) | 84.6% |
| Iceland | — | 92.0% (2016) | 93.6% |
| Poland | — | 91.5% (2024) | 91.6% |
| France | — | 91.1% (2024) | 87.3% |
| Lithuania | — | 90.6% (2024) | 90.4% |
| Czechia | — | 90.0% (2024) | 88.4% |
| Netherlands | — | 89.0% (2024) | 90.6% |
| Ireland | — | 87.2% (2021) | 86.9% |
| Slovakia | — | 86.7% (2024) | 90.5% |
| Croatia | — | 86.1% (2024) | 89.7% |
| Spain | — | 84.5% (2024) | 83.9% |
| Belgium | — | 83.9% (2024) | 88.5% |
| Greece | — | 82.9% (2024) | 82.3% |
| Italy | — | 82.9% (2024) | 84.7% |
| Peru | — | 80.5% (2024) | 81.7% |
| Türkiye | — | 72.6% (2016) | 72.9% |
Source: OECD, Education at a Glance. Adults aged 25–64 with tertiary education; latest year available, full-time earners where published. Values are for the whole field of study, not this subject alone.
Is a data science degree right for you?
It may suit you if
- You enjoy mathematics and statistics and want to use them on real problems.
- You like programming and finding patterns in information.
- You are curious about many fields, from health to sport to business.
Think twice if
- You dislike statistics, as it is the foundation of the subject.
- You expect the work to be mostly about AI, when much of it is cleaning and preparing data.
- You find long periods of detailed computer work tiring.
Further study
Master's degrees in data science, statistics, machine learning or artificial intelligence are very common and help for specialist or research roles. A PhD is often expected for research posts in AI labs and universities. Graduates who want to become actuaries take professional exams while working. Many data professionals keep learning through online courses and certifications in cloud or analytics tools, because the tools change quickly.
Questions about studying data science
What jobs can you get with a data science degree?
Common jobs include data scientist, data analyst, business analyst, data engineer, business intelligence analyst and AI engineer. Graduates with strong statistics become statisticians, and some become actuaries after professional exams. Others work in quantitative finance, marketing analytics, sports analytics, public health, fraud detection and research across many industries.
What is the difference between data science and computer science?
Computer science is broader and focuses on how software and computer systems work, including programming, algorithms, networks and security. Data science focuses on using statistics, programming and machine learning to answer questions with data. Data science usually has more statistics and less systems design, and both degrees lead to data and AI careers.
Do you need to be good at maths to study data science?
Yes, you need to be comfortable with mathematics. Statistics, probability, linear algebra and calculus are central to the subject, especially for machine learning. You do not need to be a mathematician, but most programmes expect good school mathematics, and you will use it every week.
Will AI replace data scientists?
AI tools already automate parts of the work, such as writing code, cleaning data and building standard models. This changes the job rather than removing it. People who can define the right questions, check results, understand statistics and explain findings to decision-makers are likely to remain in demand, but employers expect more from junior staff.
Related subjects
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Computer science
A computer science degree teaches how software, data and computer systems work, from programming and algorithms to networks and artificial intelligence.
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Mathematics
A mathematics degree develops advanced reasoning and problem-solving through pure mathematics, such as algebra and analysis, and applied areas, such as statistics, modelling and computing.
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Economics
An economics degree studies how people, businesses and governments make choices with limited resources, and how markets, money and policy affect jobs, prices and growth.
Sources
- OECD — Education at a Glance, labour-market outcomes — Earnings and employment by field of study, adults 25–64
- UNESCO — ISCED-F 2013 — ISCED-F 0542, 0613
How to cite this page: CourseToJob (2026). What can you do with a data science degree? Jobs and salaries. https://coursetojob.com/subjects/data-science/ (accessed September 26, 2026)