Data Scientist vs Software Engineer salary in the United States: where the gap actually shows up
In the United States, a software engineer median of US$135,980 sits about 13% above a data scientist at US$120,230 — a US$15,750 gross gap. Both seats are technology titles, so the cash gap is usually seniority, company type, and scope — not “tech vs non-tech.”
Data Scientist: Data scientists turn raw data into insight using statistics, machine learning, and clear communication. Covered United States median US$120,230 a year.
Software Engineer: Software engineers design, build, and maintain the applications and systems that power modern businesses. Covered United States median US$135,980 a year.
At entry (10th) the gap is about US$15,220 a year; at senior (90th) it is about US$15,540. If those gaps are much wider than the median gap, the titles are different careers that share a comparison page.
The United States shows about 2.9% CPI inflation in 2024. A raise that trails that rate is a real-pay cut even if you stay “ahead” of the other title on this page. Many top cash roles in the United States still run through employer sponsorship and specialty licensing. Use city salary pages when the two offers are in different metros — national medians hide local premiums.
When the higher median is the wrong decision
Cash favors Software Engineer in this United States snapshot, but training time, hours, licensing, and burnout are not in the table. If the day-to-day of Data Scientist is what you want, a 13% median gap is a negotiation input — not an instruction to switch titles.
Convert both medians through the take-home calculator with the same assumptions, then pressure-test housing with the cost-of-living tool if the jobs are in different cities.
How to read this Data Scientist vs Software Engineer table
Percentiles on this page are national United States sketches from the median and each occupation’s spread model — not a promise of what one employer pays. City pages with observed percentiles are stronger when you already know the metro.
Skills commonly listed for data scientist include Python, SQL, Statistics, and Machine learning; for software engineer, JavaScript, Python, System design, and Git. Overlap does not mean the jobs are interchangeable.