Strong long-run earnings and a broad destination map — but the data is thinner than the field feels
Data analytics looks like a high-ROI bet on the long tail: Census PSEO puts the 10-year median at $148,888 and the 75th percentile at $199,462 — among the highest in the catalog at any tier — and BLS 2024–2034 projects +10.0% weighted employment growth across destination occupations with roughly 338,000 annual openings. The destination map is unusually broad for a computing major, stretching from management analysts (1.08M employed) to data scientists (+33.5% growth) to financial managers ($161,700 median wage). The honest caveats are substantial. College Scorecard publishes no field-level earnings or debt at any credential tier — the fieldLevelSparse flag is true across all six categories — so debt-to-income ratios cannot be computed for this field. The credential mix is also atypical: 8,340 master's completions versus only 1,789 bachelor's and 32 associate's, which reflects data analytics functioning largely as a graduate specialization on top of other undergraduate degrees rather than as a standalone bachelor's path. Completions doubled from 6,912 in 2023 to 12,316 in 2024, a sign the major is still settling into the credential landscape.
- ROI A−
- Employment A
- Debt burden B
- Projected demand A−
Data analytics is a newer major with unusually strong long-run signals and unusually thin short-run data. Census PSEO shows a 10-year median of $148,888, with the 75th percentile at $199,462 and the 25th percentile at $76,015 — a long-run trajectory that sits at the top of the catalog. BLS 2024–2034 projections show +10.0% weighted employment growth across the destination occupations versus the +4.0% all-occupations baseline, with roughly 338,000 annual openings — deeper demand than almost any other computing field in the dataset.
The caveats are structural rather than negative. College Scorecard publishes no field-level year-1 earnings and no field-level debt at any credential tier — the fieldLevelSparse flag is true across all six credential categories. That means debt-to-income ratios, the usual ROI anchor on these pages, cannot be calculated directly. The $21,795 debt figure used here is an institution-level average across the 369 schools producing data analytics credentials. The major is also master's-dominated: 8,340 master's completions in 2024 versus only 1,789 bachelor's and 32 associate's, reflecting a field that currently operates more as a graduate specialization than as a standalone undergraduate path.
Completions grew sharply — 12,316 total in 2024, nearly double the 6,912 in 2023 — as the CIP code continues to absorb programs that previously classified under statistics, business analytics, or general computer science. The underlying skills (SQL, Python/R, statistics, ML, visualization) have been priced by employers for a decade under other labels; the major is the packaging, not the content. The rest of this page breaks down what the data does and doesn't say at each credential tier.
- ✓ Census PSEO shows a 10-year median of $148,888, with the 75th percentile clearing $199,462 — among the highest long-run medians in the catalog.
- ✓ BLS weighted employment growth is +10.0% for 2024–2034 — roughly 2.5× the +4.0% all-occupations baseline — with ~338k annual openings.
- ✓ Data scientists (SOC 15-2051) are projected to grow +33.5% through 2034 at a $112,590 median wage — the fastest-growing destination in the crosswalk.
- ✓ The destination map spans management analysts (1.08M employed), market research analysts (941k), financial managers (868k, +14.8%), and data scientists — unusually broad exit optionality.
- ✓ Three-year loan default rate across the 369 institutions producing data analytics credentials is 0.0% — effectively no repayment distress.
- ! College Scorecard publishes no field-level year-1 earnings for data analytics at any credential tier — year-1 ROI math cannot be verified from Scorecard alone.
- ! Scorecard field-level debt is null across all six credential categories; the $21,795 figure is an institution-level fallback spanning 369 schools.
- ! Only 1,789 bachelor's completions in 2024 (14.5% of the total) — the major operates primarily at the master's tier, limiting undergraduate-path data.
- ! Computer programmers (SOC 15-1251), one of the listed destinations, are projected to shrink -6.0% through 2034 — the only contracting occupation in the crosswalk.
- ! Total completions roughly doubled from 6,912 (2023) to 12,316 (2024). The CIP is still stabilizing, so labor-market outcomes data lags the field's current scale.
Where data analytics graduates actually land
Census Post-Secondary Employment Outcomes (PSEO)
Earnings by credential level
College Scorecard field-level earnings (years 1–4 post-grad, aggregated across institutions)
What it costs, what you earn, what's left over
The debt picture for data analytics has to be read with a caveat attached to every number. College Scorecard publishes no field-level debt at any of the six credential tiers — undergraduate certificate, associate's, bachelor's, master's, doctoral, and graduate certificate all return null, with dataSparse: true across the board. The $21,795 figure used throughout this page is an institution-level median across the 369 schools producing data analytics credentials. It does not separate a two-year community-college associate's from a Wharton master's, and it almost certainly understates borrowing at the graduate tiers where most graduates sit.
The consequence: debt-to-income ratios cannot be computed for this field at any credential level. Every ratio field in the debt-to-income breakdown is null because Scorecard also publishes null year-1 earnings at every tier. That's a significant gap — on most majors, the debt-to-income ratio at the bachelor's level is the single cleanest signal of whether the credential pays off. For data analytics, that signal is unavailable, and the analysis has to lean on adjacent data: Census PSEO's 10-year earnings trajectory, BLS destination wages, and completions-weighted expectations about where the credentials land.
What the institution-level data does say is reassuring at the margins. The three-year loan default rate across data-analytics-producing institutions is 0.0% — effectively zero repayment distress, consistent with a graduate-heavy population that earns well in the labor market. The average mid-income net price at these institutions is $17,843, which is in the normal range for four-year schools and skews somewhat low because many of the producing institutions are public master's-granting universities. None of this is a substitute for field-level numbers, but the absence of distress signals is the relevant negative finding: nothing in the institutional data suggests data analytics graduates are drowning in debt.
The credential paths that actually produce graduates
Scorecard field-level earnings + completions_by_program (most recent year) aggregated by credential tier
Associate's in Data Analytics
A two-year program covering statistics, spreadsheet and SQL fundamentals, business intelligence tools, and introductory data visualization. Produces only 32 graduates per year across 13 institutions nationwide — a vanishingly thin slice of the field. Scorecard publishes no field-level earnings at this tier.
- Completions / yr 32
- Year-1 earnings —
- Year-4 earnings —
- Median debt $21,795
- % women 50.0%
- Schools 13
Best treated as a transfer credential toward a bachelor's in analytics, business, or computer science. The freestanding analyst job market at this tier is not deep enough to defend the credential as terminal.
Bachelor's in Data Analytics (BS/BA)
A four-year program typically covering probability and statistics, databases and SQL, Python or R for analytics, machine learning fundamentals, data visualization, and a capstone. Produces 1,789 graduates across 135 institutions — small relative to adjacent majors like CS (44,627) or business analytics parents. Scorecard publishes no field-level year-1 earnings, but the BLS destination mix is predominantly bachelor's-level.
- Completions / yr 1,789
- Year-1 earnings —
- Year-4 earnings —
- Median debt $21,795
- % women 36.9%
- Schools 135
The right entry point for students targeting analyst roles — marketing analysts, financial analysts, business analysts, junior data analysts — where a bachelor's plus demonstrated SQL/Python work is the typical floor.
Master's in Data Analytics (MS)
A one-to-two-year graduate program specializing in machine learning, econometrics, experimentation, or applied domains like finance or healthcare analytics. Produces 8,340 graduates per year — the dominant credential in this field, more than 4.6× the bachelor's volume. Census PSEO's strong 10-year medians almost certainly reflect the master's-heavy credential mix.
- Completions / yr 8,340
- Year-1 earnings —
- Year-4 earnings —
- Median debt $21,795
- % women 43.1%
- Schools 123
The practical path for students targeting data-scientist, senior-analyst, or analytics-manager roles, or pivoting from a non-quantitative undergraduate degree. Fit is strongest when the master's is funded, employer-sponsored, or at a cost-competitive public program.
Doctoral (PhD) in Data Analytics
A four-to-six-year research degree producing analytics researchers for academia and industrial labs. Produces only 11 graduates per year across 4 institutions — the thinnest doctoral volume in the catalog. Overlaps substantially with statistics and data-science PhDs.
- Completions / yr 11
- Year-1 earnings —
- Year-4 earnings —
- Median debt $21,795
- % women 63.6%
- Schools 4
A niche path for students wanting an academic research career in analytics methodology. Most industry research roles are accessible through statistics, computer-science, or operations-research doctorates with deeper ecosystems.
The master's is the dominant credential and where the long-run earnings live; the bachelor's is a legitimate analyst on-ramp but carries less data. The associate's and doctoral tiers are both too thin to recommend as destinations — use the associate's as a transfer stop, and pursue a statistics or CS PhD over a data-analytics PhD if research is the goal.
Data analytics has the most master's-heavy credential distribution of any major profiled on this site. Master's degrees account for 8,340 completions — 67.7% of the field's 12,316 total — while bachelor's degrees contribute only 1,789 (14.5%) and associate's a negligible 32 (0.3%). Postbaccalaureate and post-master certificates add another 2,144 combined, and doctoral production is 11 per year across 4 institutions. This is not the shape of an undergraduate-first field; it is the shape of a graduate specialization that undergraduates access through adjacent majors (CS, statistics, business, economics) and then specialize into at the master's level.
The earnings-by-credential breakdown is empty across the board — Scorecard's fieldLevelSparse flag fires at every tier, so the per-tier earnings that anchor most credential comparisons are not available. What can be said with confidence is that PSEO's strong long-run signals ($148,888 median at year 10) reflect the dominant master's-tier cohort, not a bachelor's-first population. The bachelor's tier, with 1,789 annual graduates across 135 institutions, is legitimate but thin; the associate's tier, with 32 graduates across 13 institutions, is too small to defend as a terminal credential.
The gender composition shifts meaningfully across tiers. Overall the field is 57.6% men and 42.4% women — more balanced than computer science (75.6% men) or mechanical engineering. The bachelor's tier is the most male-skewed at 63.1% men (36.9% women), while the master's tier is nearly even at 56.9% men (43.1% women), and the thin doctoral tier actually skews 63.6% women. The completion trend is also striking: 12,316 in 2024 up from 6,912 in 2023 — a 78% one-year jump as the CIP absorbs programs that previously classified under statistics or business analytics. Expect the credential distribution to keep shifting as the bachelor's share grows relative to the graduate tiers over the next several years.
Who completes these degrees
IPEDS completions_by_program, most recent year, first-major only
- 2023 6,912
- 2024 12,316
Where graduates land professionally
BLS 2024–2034 Employment Projections via CIP-to-SOC crosswalk
| SOC | Occupation | Employed '24 | Growth | Openings/yr | Median wage | Entry |
|---|---|---|---|---|---|---|
| 13-1111 | Management analysts | 1.1M | +8.8% | 98k | $101,190 | Bachelor's degree |
| 13-1161 | Market research analysts and marketing specialists | 942k | +6.7% | 87k | $76,950 | Bachelor's degree |
| 11-3031 | Financial managers | 869k | +14.8% | 75k | $161,700 | Bachelor's degree |
| 13-2051 | Financial and investment analysts | 369k | +5.7% | 25k | $101,350 | Bachelor's degree |
| 15-2051 | Data scientists | 246k | +33.5% | 23k | $112,590 | Bachelor's degree |
| 25-1199 | Postsecondary teachers, all other | 183k | +1.8% | 14k | $78,490 | Doctoral or professional degree |
| 15-1251 | Computer programmers | 121k | -6.0% | 5.5k | $98,670 | Bachelor's degree |
| 25-1011 | Business teachers, postsecondary | 103k | +5.7% | 8.1k | $97,270 | Doctoral or professional degree |
| 15-2041 | Statisticians | 32k | +8.5% | 2.0k | $103,300 | Master's degree |
The destination map for data analytics is unusually broad — nine distinct SOC codes in the crosswalk spanning management, finance, research, and computing — which makes the field more like an applied analytical track than a tight vocational major. The largest destination is management analysts (SOC 13-1111) at 1.08 million employed, projected to grow +8.8% through 2034 with a $101,190 median wage and a remarkable 98,100 annual openings — by itself roughly 29% of the field's total annual openings. Management analyst roles are bachelor's-level entry points and absorb the majority of general-purpose analytics graduates who work in consulting or internal corporate analytics.
The second volume tier is market research analysts and marketing specialists (SOC 13-1161) at 942k employed, +6.7% growth, $76,950 median, 87k annual openings — also bachelor's entry and heavily populated by data analytics, marketing, and business-analytics graduates. Together, these two occupations account for ~185k annual openings — more than half the field's total demand — and both are growing above the +4.0% all-occupations baseline. The salary gap between them is real: management analysts earn roughly $24,000 more per year on median, reflecting the consulting premium.
The growth and premium tier is where the field's long-run earnings come from. Data scientists (SOC 15-2051) lead growth at +33.5% with a $112,590 median — the steepest projected growth of any destination in the crosswalk, and typical education is a bachelor's. Financial managers (SOC 11-3031) are the highest-paid destination at $161,700 median with +14.8% growth — a senior-track role reached with 8–12 years of analytics and finance experience. Statisticians (SOC 15-2041, +8.5%, $103,300) are small but a natural master's-level destination. The weakness in the crosswalk is computer programmers (SOC 15-1251) at -6.0% through 2034 — the only contracting occupation listed, though with only 5.5k annual openings it's a minor share of the destination map. Postsecondary teachers (SOC 25-1199, +1.8%) is academia-only and requires a doctoral, not a realistic target for most graduates. The strategic pattern is clear: most graduates enter as management analysts or market research analysts; the ambitious ones target data scientist; the seniors target financial manager.
Where demand is growing
State workforce agencies publish their own 10-year projections for management analysts — growth varies sharply by state, and where you plan to live changes the calculus.
| Washington | +31.3% | 5,370 openings/yr |
| Utah | +28.2% | 840 openings/yr |
| GU | +25.0% | 20 openings/yr |
| Tennessee | +24.8% | 1,180 openings/yr |
| Texas | +23.8% | 4,450 openings/yr |
| Wyoming | +23.7% | 40 openings/yr |
| Colorado | +20.4% | 1,580 openings/yr |
| Oregon | +20.3% | 1,070 openings/yr |
| California | 12,080/yr | +9.3% growth |
| Florida | 7,750/yr | +19.0% growth |
| Virginia | 7,410/yr | +10.1% growth |
| Washington | 5,370/yr | +31.3% growth |
| Illinois | 5,000/yr | +6.3% growth |
Where management analysts need a license
11 states and territories license management analysts. The degree alone isn't the finish line — plan for the credential your state requires before you can practice.
Schools producing the most graduates
Volume, not quality — completion counts across all credentials. See our rankings pages for outcome-weighted school scores.
- 1,288
- 737
- 594
- 490
- 428
- 6379
- 274
- 271
- 250
- 10246
Pursue data analytics at the master's level when it is the clearest credential fit — especially layered onto a quantitative undergraduate degree (statistics, economics, computer science, or math) — and when funded, employer-sponsored, or at a cost-competitive public program. The master's is where the field's strength shows up: 8,340 annual graduates, Census PSEO's $148,888 10-year median heavily reflecting this cohort, and a destination map that includes data scientists (+33.5% growth, $112,590 median) and statisticians ($103,300 median) where a graduate degree is the typical or expected entry point. Expect institutional borrowing to be higher than the $21,795 institution-level fallback for private master's programs — the field-level debt data is missing, so plan conservatively.
The bachelor's is a legitimate analyst on-ramp but comes with thinner data. The 1,789 annual graduates across 135 institutions are a small cohort relative to adjacent majors, and College Scorecard publishes no field-level year-1 earnings at this tier, so ROI math has to lean on the destination map rather than direct earnings aggregates. That destination map is favorable at the bachelor's level — management analysts, market research analysts, financial analysts, and (with the right technical depth) junior data analysts are all bachelor's-typical entries with ~185k combined annual openings at +6.7% to +8.8% growth. The realistic expectation is starting compensation in the $55k–$75k range depending on geography and employer, with substantial upside for graduates who layer on a master's or move into data science or financial manager tracks. Students choosing between data analytics and CS at the bachelor's level should choose CS if they want to build software and data analytics if they want to analyze data — the jobs and the coursework both pull in different directions despite the surface overlap.
The recommendation flips negative for two cases. First: the associate's tier. With 32 annual graduates across 13 institutions and no Scorecard earnings data, the credential is too thin to defend as a terminal qualification. Treat it as a transfer on-ramp to a bachelor's in analytics, business, or computer science — not a destination. Second: the doctoral tier. With 11 annual graduates across 4 institutions, the data-analytics PhD is the smallest doctoral path in the catalog. Students targeting an academic or research career in analytics methodology are almost always better served by a statistics, computer-science, or operations-research PhD, where the ecosystem of faculty, funding, and industry labs is mature. The pattern across the field is consistent: data analytics works best where the analytical skills meet real data at scale — at the master's level for specialists, at the bachelor's level for analysts, and not really anywhere else.
Informed inquiries
Is a data analytics bachelor's worth it when computer science grads earn more?
It depends on what you want to do. CS bachelor's grads earn $73,652 in year 1 per Scorecard and target software-engineer roles; data analytics Scorecard field-level year-1 earnings are null at every tier, so direct comparison is impossible. What the long-run PSEO data does show is that data analytics graduates reach a 10-year median of $148,888 — above CS's 10-year PSEO median of $114,482 — but that figure reflects a heavily master's-skewed credential mix (8,340 master's vs. 1,789 bachelor's annually), not a pure bachelor's cohort. The defensible take: if you want to build software, choose CS; if you want to be an analyst — and especially if you plan to pursue a master's — data analytics pairs cleanly with that trajectory. The destination map is broader but the bachelor's-level data is thinner.
Why is the earnings and debt data so incomplete for this major?
College Scorecard's fieldLevelSparse flag is true across all six credential categories — undergraduate certificate, associate's, bachelor's, master's, doctoral, and graduate certificate — meaning Scorecard has not yet published aggregated field-level earnings or debt for CIP 30.71 (Data Analytics). Two factors drive this. First, the CIP code is relatively new and still populating: 2024 completions of 12,316 nearly doubled from 6,912 in 2023, and Scorecard requires several post-graduation years of earnings data before publishing. Second, small-cohort suppression rules hide statistics where counts are low enough to risk identifying individuals — which bites hard at the associate's (32 completions) and doctoral (11 completions) tiers. The $21,795 debt figure throughout this page is an institution-level average across 369 data-analytics-producing schools, not a field-specific number, and should be treated as a rough anchor rather than a precise credential-tier estimate.
How does data analytics compare to data science or statistics as a major?
The three overlap heavily in practice, and labor-market destinations are nearly identical — data scientists, statisticians, market research analysts, financial analysts, and management analysts appear in all three crosswalks. Data analytics tends to skew applied and business-facing, with heavier coursework in SQL, BI tools, and visualization; statistics leans theoretical with deeper probability, inference, and experimental design; data science sits in between with more machine-learning and programming emphasis. At the graduate level, the curricula converge to the point where choice often comes down to department strength at a specific school. At the bachelor's level, data analytics programs are newer and typically housed in business schools, while statistics lives in math/stats departments and data science varies widely. If the goal is a data-scientist job with +33.5% projected growth at $112,590 median, any of the three can get there — the differentiator is coursework rigor and portfolio evidence, not the CIP code on the diploma.
Is a master's in data analytics worth the tuition if I already have a bachelor's?
Possibly — but Scorecard's field-level earnings gap prevents a clean numerical answer. What the data does say: 8,340 master's graduates per year versus 1,789 bachelor's means the master's is the field's dominant credential, and PSEO's $148,888 10-year median reflects that master's-heavy mix. The destination map improves at the graduate level — data scientists (+33.5%, $112,590 median), statisticians (+8.5%, $103,300, master's is typical entry), and financial managers ($161,700) all become realistic targets with an analytics master's layered on a quantitative undergraduate degree. The caveat is cost: at the institution-level average net price of $17,843 mid-income (which skews undergraduate), a public master's can be reasonable, but private one-year master's programs at $60k+ will eat most of the salary premium for years. Fully-funded master's programs, employer tuition reimbursement, or low-cost public options are the strongest cases.
Which occupations should data analytics graduates actually target?
The BLS destination map is broad but clearly tiered. The volume leaders are management analysts (SOC 13-1111, 1.08M employed, +8.8% growth, $101,190 median, 98k annual openings) and market research analysts (SOC 13-1161, 942k employed, +6.7%, $76,950 median, 87k openings) — both bachelor's-level entry points. The premium growth tier is data scientists (SOC 15-2051, +33.5%, $112,590 median) — by far the fastest-growing destination. Financial managers (SOC 11-3031, +14.8%, $161,700) are the senior-track destination reachable with 8–12 years of experience. The weaker destinations are computer programmers (-6.0% — the only contracting occupation listed) and postsecondary teachers (+1.8%, doctoral-required, thin pay). The strategic pattern is straightforward: analyst roles (management, market research, financial) are the realistic entry points; data scientist is the growth aspiration; financial manager is the long-term destination.
The major is new — should I wait for better data before picking it?
No, but calibrate accordingly. The CIP (30.71) is newer and Scorecard field-level outcomes haven't caught up — you're committing on thinner data than you would for CS or accounting. That said, the underlying skills (SQL, Python/R, statistics, visualization, ML) are the same ones the labor market has priced highly for a decade under other labels (statistics, business analytics, data science). A bachelor's in data analytics from a reputable program should feed the same analyst job market that statistics and business-analytics bachelor's graduates enter, whether or not Scorecard's field-level aggregates arrive on schedule. The practical hedge: prioritize portfolio evidence (Kaggle, GitHub, internships, capstone projects) over the major label, and confirm that the specific program's curriculum covers SQL, Python or R, statistics through regression, and at least one ML course. If the curriculum looks thin on those, the major label won't rescue it — and an adjacent statistics or CS degree becomes the better bet.
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