Skill path
How to become a Data Scientist
How to become a Data Scientist: skill roadmap with 5 core skills, degree usually required, courses and salary data. Updated weekly.
Education & experience requirements
- Education
- Most of these occupations require a four-year bachelor's degree, but some do not.
- Experience
- A considerable amount of work-related skill, knowledge, or experience is needed for these occupations.
- On-the-job training
- Employees in these occupations usually need several years of work-related experience, on-the-job training, and/or vocational training.
Foundations
Skills assumed by employers — the base to build on
- StatisticsFoundation
Collecting and interpreting numerical data. Employers need it to draw conclusions from data. Learn through study and hands-on analysis of datasets.
- ProbabilityFoundation
Mathematical study of randomness. Employers need it for statistical models and risk assessment. Learn through courses and applied problems.
- Linear algebraFoundation
- Programming (Python, R)Foundation
Writing code for data manipulation and analysis. Employers need custom analytical solutions. Learn by coding regularly and working on projects.
- Database managementFoundation
Storing, updating, and retrieving data efficiently. Employers need organized data access. Learn through SQL and database tools.
Core skills
The skills that define the role today
- PythonHigh demand
A versatile programming language. Data professionals use it for analysis, automation, and building data-driven applications.
- SQLHigh demand
A language for managing and querying databases. Analysts and engineers use it to extract and analyze data from various sources.
- StatisticsHigh demand
Collecting and interpreting numerical data. Employers need it to draw conclusions from data. Learn through study and hands-on analysis of datasets.
- ExperimentationHigh demand
Conducting controlled tests to gather data. Professionals use this to validate hypotheses and optimize processes or products.
- Machine LearningHigh demand
AI that learns from data to make predictions or decisions. Used by scientists and managers to analyze complex data and automate tasks.
Tools in demand
Specific tools that appear in live postings
- AWSIn demand
Amazon's cloud platform for computing, storage, and services. Employers use it for scalable infrastructure. Learn by experimenting with AWS free tier and following official documentation.
- CIn demand
A low-level programming language for system and embedded development. Valued for performance-critical applications. Learn by writing C programs and studying memory management.
- C++In demand
An object-oriented language for high-performance software. Needed for game engines, systems, and large applications. Gain through practical projects and C++ guides.
- SASIn demand
Statistical analysis software used for advanced analytics. Employers use it to process data and generate reports. Learn through documentation and practice.
- HadoopIn demand
A framework for storing and processing large datasets across clusters. Employers need it to handle big data. Learn by setting up clusters and using its tools.
- RIn demand
A programming language for statistical computing. Data scientists and managers use R for data analysis, visualization, and modeling.
- TensorFlowIn demand
A framework for building and training neural networks. Used in machine learning and data science. Develop skills through hands-on model building and community resources.
- StatisticsIn demand
Collecting and interpreting numerical data. Employers need it to draw conclusions from data. Learn through study and hands-on analysis of datasets.