Data Scientist

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Job Outlook:
Much faster than average
Education: Bachelor's degree
High: $174,790.00
Average: $115,240.00
Average: $55.40

What they do:

Develop and implement a set of techniques or analytics applications to transform raw data into meaningful information using data-oriented programming languages and visualization software. Apply data mining, data modeling, natural language processing, and machine learning to extract and analyze information from large structured and unstructured datasets. Visualize, interpret, and report data findings. May create dynamic data reports.

On the job, you would:

  • Analyze, manipulate, or process large sets of data using statistical software.
  • Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
  • Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.

Important Qualities

Analytical skills. Data scientists must be adept at researching and at examining and interpreting findings.

Computer skills. Data scientists must be able to write code, analyze data, develop or improve algorithms, and use data visualization tools.

Communication skills. Data scientists must be able to convey the results of their analysis to technical and nontechnical audiences to make business recommendations.

Logical-thinking skills. Data scientists must understand and be able to design and develop statistical models and to analyze data.

Math skills. Data scientists use statistical methods to collect and organize data.

Problem-solving skills. Data scientists must devise solutions to the problems they encounter in data collection and cleaning and in developing statistical models and algorithms.

Job Details

Analyze data to inform operational decisions or activities.
Analyze business or financial data.
Determine appropriate methods for data analysis.
Prepare data for analysis.
Prepare graphics or other visual representations of information.
Prepare analytical reports.
Present research results to others.
Develop procedures to evaluate organizational activities.
Select resources needed to accomplish tasks.
Analyze data to identify trends or relationships among variables.
Analyze data to identify or resolve operational problems.
Apply mathematical principles or statistical approaches to solve problems in scientific or applied fields.
Update technical knowledge.
Advise others on analytical techniques.
Develop scientific or mathematical models.
Write computer programming code.

What Data Scientists Do

To present their findings, these scientists often make use of data visualization.

Data scientists use analytical tools and techniques to extract meaningful insights from data.


Data scientists typically do the following:

  • Determine which data are available and useful for the project
  • Collect, categorize, and analyze data
  • Create, validate, test, and update algorithms and models
  • Use data visualization software to present findings
  • Make business recommendations to stakeholders based on data analysis

Data scientists often begin a project by gathering or identifying relevant data sources, such as surveys. They may use a variety of methods to obtain data, including through access to other organizations’ databases or by using web-scraping tools (software that extracts specific information from websites). They may start with large, unstructured datasets, commonly referred to as raw data. To properly analyze the data, these scientists must “clean” the raw data, a process by which they structure the data to make them readable by software programs.

Data scientists develop algorithms (sets of instructions that tell computers what to do) and models to support programs for machine learning. They use machine learning to classify or categorize data or to make predictions related to the models. Scientists also must test the algorithms and models for accuracy, including for updates with newly collected data.

Data scientists often use data visualization software to present their findings as charts, maps, and other graphics. Visualization techniques allow data scientists to clearly communicate their analyses to technical and nontechnical audiences, including colleagues, managers, and clients. Ensuring that audiences understand the information helps data scientists make recommendations for business decisions or process changes based on the results of their analysis.

Some data scientists choose to focus on a particular area of work. For example, data scientists who have a strong coding or engineering background may develop or recommend systems, build machine learning algorithms, and devise ways to enhance web-browsing functions. Others conduct research for reports or academic journals. Still others focus on improving business strategy for activities such as marketing, sales, and user engagement.

Work Environment

Data scientists held about 168,900 jobs in 2022. The largest employers of data scientists were as follows:

Computer systems design and related services 13%
Insurance carriers and related activities 9
Management of companies and enterprises 8
Management, scientific, and technical consulting services 7
Scientific research and development services 5

Data scientists spend much of their time in an office setting.

Work Schedules

Most data scientists work full time.

Getting Started


How to Become a Data Scientist

Data scientists need strong computer skills.

Data scientists typically need at least a bachelor’s degree in mathematics, statistics, computer science, or a related field to enter the occupation. However, some employers require or prefer that candidates have a master’s or doctoral degree.


Data scientists typically need at least a bachelor’s degree, but some jobs require a master’s or doctoral degree. Common fields of degree include mathematics, statistics, computer science, business, and engineering.

Because data science involves the use of algorithms and statistical techniques, students need extensive study in mathematics and statistics. High school students interested in becoming data scientists should take classes in subjects such as linear algebra, calculus, and probability and statistics.

At the college level, courses in computer science are important in addition to math and statistics. Students must learn data-oriented programming languages as well as statistical, database, and other software for presenting analyses.

Other Experience

Some employers require industry-related experience or education. For example, data scientists seeking work in an asset management company may need to have experience in the finance industry or to have completed coursework that demonstrates an understanding of investments, banking, or related subjects.

Job Outlook

Employment of data scientists is projected to grow 35 percent from 2022 to 2032, much faster than the average for all occupations.

About 17,700 openings for data scientists are projected each year, on average, over the decade. Many of those openings are expected to result from the need to replace workers who transfer to different occupations or exit the labor force, such as to retire.


Employment growth for data scientists is expected to stem from an increased demand for data-driven decisions. The volume of data available and the potential uses for that data will increase over the projections decade. As a result, organizations will likely need more data scientists to mine and analyze the large amounts of information and data collected. Data scientists’ analysis will help organizations to make informed decisions and improve their business processes, to design and develop new products, and to better market their products. 

Contacts for More Information

For more information about data scientists, visit

Academic Data Science Alliance

Institute for Operations Research and the Management Sciences

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