Data Scientists

Summary

What Data Scientists Do About this section

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.

Duties

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 About this section

Data scientists typically work in an office setting.

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

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

Work Schedules

Most data scientists work full time.

How to Become a Data Scientist About this section

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.

Education

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.

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.

Pay About this section

The median annual wage for data scientists was $108,020 in May 2023. The median wage is the wage at which half the workers in an occupation earned more than that amount and half earned less. The lowest 10 percent earned less than $61,070, and the highest 10 percent earned more than $184,090.

In May 2023, the median annual wages for data scientists in the top industries in which they worked were as follows:

Most data scientists work full time.

Job Outlook About this section

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

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. 

State & Area Data About this section

Occupational Employment and Wage Statistics (OEWS)

The Occupational Employment and Wage Statistics (OEWS) program produces employment and wage estimates annually for over 800 occupations. These estimates are available for the nation as a whole, for individual states, and for metropolitan and nonmetropolitan areas. The link(s) below go to OEWS data maps for employment and wages by state and area.

• Data scientists

Projections Central

Occupational employment projections are developed for all states by Labor Market Information (LMI) or individual state Employment Projections offices. All state projections data are available at www.projectionscentral.org. Information on this site allows projected employment growth for an occupation to be compared among states or to be compared within one state. In addition, states may produce projections for areas; there are links to each state’s websites where these data may be retrieved.

CareerOneStop

CareerOneStop includes hundreds of occupational profiles with data available by state and metro area. There are links in the left-hand side menu to compare occupational employment by state and occupational wages by local area or metro area. There is also a salary info tool to search for wages by zip code.

Contacts for More Information About this section

For more information about data scientists, visit

Academic Data Science Alliance

Institute for Operations Research and the Management Sciences

O*NET

Business Intelligence Analysts

Clinical Data Managers

Data Scientists