Data Analyst vs. Data Scientist: Key Differences Explained
Both titles sit inside the same federal occupation code, which shapes what the published pay data shows and where the two jobs really diverge in practice.
Quick answer
- Published pay is the same for both: the median annual wage for data scientists, the parent occupation covering business intelligence analysts, was $120,230 in May 2025 (U.S. Bureau of Labor Statistics, 2025).
- Entry requirements differ in degree, not in kind: both sit in O*NET Job Zone Four, which typically calls for a four-year bachelor's degree, but some employers require or prefer a master's or doctoral degree for data scientist roles (U.S. Bureau of Labor Statistics, 2025).
- Daily work splits on modelling: data scientists create, validate, test and update algorithms and models (U.S. Bureau of Labor Statistics, 2025), while analyst work centres on recurring reporting, dashboards and stakeholder questions answered from existing data.
A data analyst explains what has already happened in a business's data; a data scientist builds and tests models that estimate what will happen next. In federal statistics the two are not separated: Business Intelligence Analysts (15-2051.01) is listed as a specialty under the Data Scientists occupation (15-2051.00) in O*NET.
So pay and growth figures look identical on paper, and the real differences show up in hiring requirements, the tools you use, and what lands in your queue on a Monday morning.
Side-by-Side Comparison
Because O*NET classifies Business Intelligence Analysts (15-2051.01) as a specialty within Data Scientists (15-2051.00), the published wage and growth figures for the two are the same figures.
| Category | Data Analyst (Business Intelligence Analysts, 15-2051.01) | Data Scientist (15-2051.00) |
|---|---|---|
| Median pay | $120,230 a year, or $57.80 an hour, reported for the parent occupation Data Scientists (U.S. Bureau of Labor Statistics, May 2025) | $120,230 a year, or $57.80 an hour (U.S. Bureau of Labor Statistics, May 2025) |
| Typical education | ONET Job Zone Four: typically a four-year bachelor's degree plus considerable work-related experience (ONET OnLine, U.S. Department of Labor) | At least a bachelor's degree in mathematics, statistics, computer science or a related field, with some employers requiring or preferring a master's or doctoral degree (U.S. Bureau of Labor Statistics, 2025); also Job Zone Four |
| Experience and training | Considerable work-related experience expected for the job zone; a Registered Apprenticeship title has been vetted for this code (O*NET OnLine) | Work experience in a related occupation plus on-the-job training typically needed (U.S. Bureau of Labor Statistics, 2025); Registered Apprenticeship titles listed for the code (O*NET OnLine) |
| Physical demands | Sedentary: the O*NET work context survey covers time spent sitting, indoor work and the importance of being exact or accurate | Sedentary: the O*NET survey likewise covers sitting and indoor work, and most spend much of their time in an office setting (U.S. Bureau of Labor Statistics, 2025) |
| Schedule type | Most work full time (U.S. Bureau of Labor Statistics, 2025), shaped by reporting cycles such as month-end and quarter-end close | Most work full time (U.S. Bureau of Labor Statistics, 2025), shaped by project and model-release deadlines |
| Growth outlook | 7% or higher for 2025–2035, much faster than average, with 24,800 projected annual openings (O*NET OnLine, sourced to U.S. Bureau of Labor Statistics, 2025) | Same source and occupation: employment of 275,600 and projected 2025–2035 growth of 7% or higher (O*NET OnLine, sourced to U.S. Bureau of Labor Statistics, 2025) |
Treat the pay row as a national midpoint for the combined occupation, not a starting offer. Check current figures for your state and metro area on the BLS Occupational Employment and Wage Statistics pages, since the same title pays differently across states and industries.
Day-to-Day Differences
The clearest contrast is the first hour of the day.
A data analyst usually opens with the overnight refresh: checking that scheduled jobs loaded without error, opening the dashboards business users rely on in a BI tool, and looking for figures that moved more than expected. A regional sales number that halved overnight is more often a broken join than a collapse in demand. Then comes the request queue — finance wants last quarter's revenue split a new way, so you write SQL against the warehouse, reconcile the total against the system of record, and rebuild the visual. Precision drives the day, and the ONET work context survey for Business Intelligence Analysts tracks exactly that: the importance of being exact or accurate (ONET OnLine, U.S. Department of Labor).
A data scientist is more likely to open a notebook and check a training run that finished overnight, comparing evaluation metrics against the previous version, inspecting where the model got things wrong, and deciding whether to change features or the algorithm. The Bureau of Labor Statistics describes the work as determining which data are available and useful, collecting and categorising it, and creating, validating, testing and updating algorithms and models (U.S. Bureau of Labor Statistics, 2025).
Both converge later: each uses data visualization software to present findings and recommend actions to stakeholders. Entry-level staff in either role spend more time preparing data; experienced staff set the question and review others' work.
Which Career Is Right for You
- Choose data analyst if you want to enter on a bachelor's degree rather than a graduate one. Both roles sit in O*NET Job Zone Four, but it is specifically data scientist roles where some employers require or prefer a master's or doctoral degree (U.S. Bureau of Labor Statistics, 2025).
- Choose data analyst if you would rather have a predictable cycle of deliverables — weekly reporting, month-end and quarter-end close — than open-ended work whose end date you set.
- Choose data analyst if you want your output read the same week you produce it, by people sitting close to the decision.
- Choose data scientist if you are willing to spend time first in a related occupation: work experience in a related occupation and on-the-job training are typically needed (U.S. Bureau of Labor Statistics, 2025), so a sideways move from analyst, engineer or researcher is a common route.
- Choose data scientist if you want to own the model rather than report its output — creating, validating, testing and updating algorithms is a core duty of the occupation (U.S. Bureau of Labor Statistics, 2025).
- Choose either only if desk-based indoor work suits you: most people in the occupation spend much of their time in an office setting and work full time (U.S. Bureau of Labor Statistics, 2025).
Because the titles are used loosely, read postings in your state rather than the label. Dashboards, SQL and stakeholder reporting is analyst work whatever it is called; model deployment and experimentation is data science. Registered Apprenticeship titles have been vetted for both codes (O*NET OnLine), worth checking with your state apprenticeship office if you want an earn-while-you-learn route.
Frequently asked questions
Which pays more starting out?
Federal data cannot split the two, because both titles fall under one occupation: the median annual wage for data scientists, which includes business intelligence analysts as a specialty, was $120,230 in May 2025 (U.S. Bureau of Labor Statistics, 2025). A median is the midpoint across all experience levels, so entry-level offers typically sit below it. Roles that require a master's or doctoral degree tend to be advertised above analyst roles at the same employer.
Do I need a master's degree to be a data scientist?
Not always. The Bureau of Labor Statistics states that data scientists typically need at least a bachelor's degree in mathematics, statistics, computer science or a related field, and that some employers require or prefer a master's or doctoral degree (U.S. Bureau of Labor Statistics, 2025). O*NET places the occupation in Job Zone Four, meaning a four-year degree plus considerable work-related experience. Whether graduate study is needed depends on the employer and the research content of the role.
Can a data analyst become a data scientist?
It is one of the standard routes, because the Bureau of Labor Statistics lists work experience in a related occupation and on-the-job training as typically needed for data scientists (U.S. Bureau of Labor Statistics, 2025). Analyst work already covers determining which data are available and useful and presenting findings with visualization software; the gap is usually building, validating and testing models. Expect to add statistics and programming depth, through graduate study or modelling work inside your current job.
Which has the better job outlook?
The outlook figures are shared. O*NET, sourcing Bureau of Labor Statistics 2025 data for the Data Scientists occupation that covers both titles, reports employment of 275,600, projected 2025–2035 growth of much faster than average at 7% or higher, and 24,800 projected annual openings. Because the two titles are not counted separately, no federal figure shows one growing faster than the other.
Sources
- U.S. Bureau of Labor Statistics — Data Scientists : Occupational Outlook Handbook (2025)
- O*NET OnLine (U.S. Department of Labor) — 15-2051.00 - Data Scientists
Written by
Wyatt covers work outside the office: construction, logistics, repair, and the people who keep things running. He's skeptical of career advice that assumes everyone sits at a desk.
