Data scientist

What does a data scientist do?

• Work with managers and teams to turn business questions into problems that data can answer.
• Collect, clean and combine data from databases, files and other sources.
• Explore data and use statistical methods to test ideas and measure effects.
• Build, test and improve machine learning models for tasks such as forecasting or recommendations.
• Design and analyse experiments, for example to compare two versions of a product.
• Present results clearly with charts, reports and talks for non-specialists.
• Work with engineers to put models into real products and monitor how they perform.

Where do they work?

Data scientists work for technology companies, banks, insurers, retailers, hospitals, consultancies, research institutes, national statistics offices and public health bodies. Most work in teams with data engineers, analysts and product managers. Hybrid and remote work is common. The work is computer-based and organised around projects, with a mix of independent analysis, meetings and presentations. In smaller organisations one person may do everything from collecting data to reporting results.

What skills do you need?

• Statistics and probability
• Programming in Python or R
• SQL and working with databases
• Machine learning methods
• Data cleaning and visualisation
• Experiment design
• Explaining results to non-technical people
• Curiosity and critical thinking

Official skills profile (ESCO)

Essential skills listed for this occupation in ESCO, the European Commission's multilingual classification of skills and occupations.

• execute analytical mathematical calculations
• implement data quality processes
• interpret current data
• normalise data
• establish data processes
• manage data collection systems
• build recommender systems
• develop data processing applications
• perform data cleansing
• handle data samples
• design database scheme
• report analysis results

Essential knowledge: statistics · data models · online analytical processing · visual presentation techniques · information extraction · resource description framework query language · query languages · information categorisation

How do you become a data scientist?

Most data scientists have at least a bachelor's degree in a quantitative subject, such as mathematics, statistics, computer science, data science, physics or economics. Many employers, especially for research-heavy roles, prefer a master's degree or PhD. Practical skills matter as much as qualifications. You should be confident with Python or R, SQL and core statistics, and have projects that show how you solved real problems with data. Many people start as data analysts or software developers and move into data science with experience. Interviews often include statistics questions and a coding or case-study task.

1. University degree. A bachelor's degree in data science, statistics, mathematics, computer science or a related subject gives you the foundation. A one- or two-year master's degree in data science, statistics or machine learning is a common next step, and employers often ask for one for more advanced roles.
2. Conversion master's or PhD. Graduates in subjects such as physics, biology, psychology, economics or engineering often move into data science through a conversion master's degree. A PhD that involves a lot of data analysis or modelling is also a strong route, particularly for research and specialist machine learning roles.
3. Moving up from a related job. Many data scientists first work as data analysts, software developers or researchers and build statistics and machine learning skills on the job or through online courses. Short courses alone rarely lead straight to a data scientist role, so a portfolio and relevant work experience are important.

Degrees that lead to this career

• Data science

  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.

  6 linked careers

• 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.

  6 linked careers

• Computer science

  A computer science degree teaches how software, data and computer systems work, from programming and algorithms to networks and artificial intelligence.

  9 linked careers

• Physics

  A physics degree explores the laws that govern the universe, from particles and atoms to materials, energy and stars, using mathematics, experiments and computer models.

  6 linked careers

• 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.

  6 linked careers

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Do you need a licence to work as a data scientist?

Data science is not a regulated profession, so you do not need a licence to work as a data scientist. However, the work is shaped by data protection and privacy laws, which differ between countries and regions such as the European Union. Some governments are also introducing rules on AI and automated decisions. Professional bodies for statisticians in several countries offer voluntary accreditation for data scientists.

How much does a data scientist earn?

Pay in the United States

• $120,230Median annual wage, May 2025
• $67,240–$199,130Range from the lowest-paid 10% to the highest-paid 10%
• 262.4KPeople employed in the US

US Bureau of Labor Statistics, Occupational Employment and Wage Statistics, SOC 15-2051, May 2025. National estimates across all industries; excludes the self-employed.

Earnings of Professionals around the world

Most countries do not publish pay for single job titles. The International Labour Organization collects median monthly earnings for broad occupation groups instead. This career belongs to ISCO-08 major group 2, "Professionals". The table covers the whole group, which includes data scientist and many other occupations.

Source: ILOSTAT, median monthly earnings of employees, latest year available. PPP$ adjusts for price differences between countries so figures can be compared. "vs all employees" compares the group's median with the median for all occupations in the same country.

Career progression

1. Junior data scientist
2. Data scientist
3. Senior data scientist
4. Lead or principal data scientist
5. Head of data science or chief data officer

Job outlook

Organisations collect more data than ever and want to use it for forecasting, personalisation and automation, so data science skills remain in demand across many sectors. The role is changing. Automated machine learning and AI assistants now handle more routine modelling and coding. As a result, employers increasingly value strong statistics, knowledge of a sector, good judgement and the ability to explain results. Entry-level roles are competitive, and job titles vary widely, so read job descriptions carefully.

Questions about becoming a data scientist

Do you need a master's degree to become a data scientist?

Not always, but it helps. Many data scientists have a master's degree or PhD, and some employers list one as a requirement. Others hire graduates with a strong bachelor's degree in a quantitative subject, especially if they have relevant projects, internships or experience as a data analyst.

What is the difference between a data scientist and a data analyst?

Data analysts mainly describe what has happened, using SQL, spreadsheets and dashboards to report trends. Data scientists usually go further, building statistical and machine learning models to predict outcomes or automate decisions. In practice the titles overlap, and the difference depends on the employer.

Which degree is best for data science?

Mathematics, statistics, computer science and data science degrees are the most direct choices. Physics, economics, engineering and other subjects with a lot of statistics and programming also lead into the field. Whatever you study, take courses in statistics, programming and machine learning, and build projects with real data.

Is data science still a good career?

Data science remains a strong career in many countries, but it is more competitive and more specialised than when the field was new. Employers now expect solid statistics and engineering skills, not just knowledge of popular tools. People who combine technical skills with knowledge of a sector, such as health or finance, often have an advantage.

Related careers

• 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.

  Degree often expected

• 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.

  Degree usually needed

• Statistician

  Statisticians collect, analyse and interpret data to answer questions and support decisions.

  Degree required

• Software developer

  Software developers design, build, test and maintain the programs and apps that run on computers, phones, websites and machines.

  Degree often expected

Sources

1. US Bureau of Labor Statistics — Occupational Employment and Wage Statistics — SOC 15-2051, national estimates, May 2025
2. ILOSTAT — Median monthly earnings of employees by occupation — ISCO-08 major groups, latest year per country
3. European Commission — ESCO occupation profile — ESCO code 2511.3

How to cite this page: CourseToJob (2026). How to become a data scientist: degrees, skills and salary. https://coursetojob.com/careers/data-scientist/ (accessed September 26, 2026)

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