Description:

There were 275,600 data scientist jobs in the United States in 2025, according to the Bureau of Labor Statistics. BLS projects 371,000 by 2035, an increase of about 35%.

Gen AI could push employment either way. Making each data scientist more productive could reduce the number needed. But making analysis cheaper could increase demand enough to create more jobs.

This market asks whether employment grows above its 2025 level—not whether AI alone causes it to grow.

Explore the economics with this interactive supply-and-demand tool.

Resolution criteria:

• Primary source: BLS Employment Projections’ National Employment Matrix, which includes self-employed workers. The baseline is fixed at 275,600, the 2025 employment figure for data scientists, SOC 15-2051, reported in the Occupational Outlook Handbook.

• YES if the 2030 base-year employment estimate in the 2030–2040 matrix exceeds 275,600; NO otherwise. Earlier projections of 2030 employment do not count.

• I will use the first release of that matrix, including official corrections published by December 31, 2031.

• Classification changes: A rename or clean split is acceptable if it preserves the occupation’s scope; split categories will be summed. For broader mergers or other changes, I will use a BLS-published comparable estimate if available. If no comparable estimate exists, this will resolve N/A.

• Fallback: If the matrix is unavailable by December 31, 2031, I will compare BLS OEWS May 2030 employment with May 2025 employment for the same occupation. YES if higher; NO otherwise. I will use the figures available at that deadline, applying the same classification rule.

• If neither source provides comparable figures by that deadline, this will resolve N/A.