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Companies in virtually every industry generate vast amounts of data. Data scientists use their skills to analyze this information, helping organizations uncover insights, build strategies, and adapt to changes.
By: Thomas Broderick, Edited by: Joey Morris
Last updated: June 5, 2025
What is a data scientist?
A data scientist is a professional who analyzes and interprets large quantities of complex data to help businesses and organizations solve problems. Employers' needs determine the data collection and analysis techniques that these professionals use on the job. No matter the specifics, the work requires a strong mastery of computer science and mathematics fundamentals.
Data scientists typically earn a bachelor's or master's in data science or a related field like mathematics, statistics, and computer science.
These professionals work in various industries, such as computer systems design, insurance, management, and technical consulting organizations. According to 2023 data from the Bureau of Labor Statistics (BLS), these industries employ nearly a third of all data scientists.
Key responsibilities of data scientists
While daily tasks often differ from one role to the next, a data scientist typically has the following key responsibilities:
- Data collection and cleaning: After reviewing requirements and parameters, data scientists find and collect data from a variety of sources. Data cleaning helps to ensure accuracy and relevancy.
- Data analysis and exploration: Using statistical methods and tools, data scientists identify patterns and trends from their data to help them answer questions.
- Model building and evaluation: Data scientists develop and test predictive models and algorithms so they can solve complex business problems.
- Data visualization and communication: Informing stakeholders means creating visualizations that are accessible to individuals without a data science background. Data scientists often use specialized software to create charts and other graphics that assist in communicating their findings.
- Strategic decision and support: Data scientists present their findings and provide additional support to help inform business strategy decisions.
Essential skills for data scientists
Data scientists need more than just computer science and mathematics knowledge to succeed on the job. Transferable skills such as decision-making and communication can help these profesionals thrive in a modern business environment. The following can also benefit data scientists:
- Analytical skills help professionals discover patterns in datasets and draw conclusions.
- Business communication skills let data scientists collaborate with peers, managers, and other stakeholders.
- Logical thinking skills help data scientists develop the right models and algorithms for each project.
- Problem-solving skills let professionals identify solutions when issues arise during data collection or analysis.
A master's in data science can help you refine these and other skills while preparing you for career advancement.
Common tools and technologies used by data scientists
Data scientists use a variety of tools and software to help them manage and analyze large datasets. Common tools and technologies include data visualization software, knowledge of coding languages, and experience with machine learning and statistical, computational, and modeling programs.
Data scientists must know how to visualize and manipulate data. Programs such as Tableau and Matplotlib allow users to create charts and plots, develop interactive dashboards, and represent data visually.
Two of the most popular programming languages among data scientists are R and Python. R is commonly used in statistical analysis and data visualization. Python is a popular language in machine learning, data analysis, and automation.