IQ 130 Careers: Where high cognitive ability meets $140k+ pay

IQ Career Lab is a cognitive assessment platform that measures intelligence across five domains and matches your cognitive profile to high-fit career paths. This article answers Henry's question with the cleanest evidence we can assemble. The data is a four-source synthesis. It joins BLS Occupational Employment and Wage Statistics (May 2024), Wolfram (2023) on between-occupation cognitive variance, Wai (2013) on elite-tier figures, and Sackett et al. (2024) on the corrected validity of cognitive ability for job performance. We then steelman the single best counter-argument, the Keuschnigg, van de Rijt and Bol (2023) plateau finding, instead of burying it.

Why "IQ 130 careers" is the wrong question, and the right one

Type "iq 130 careers" into a search bar and most answers you get back conflate two different questions. The first: which occupations have an average measured IQ near 130? The second: which careers reward an individual who scores 130 with both cognitive fit and $140k+ annual mean wages? Only the second question is answerable. Wolfram's 2023 paper in Intelligence analyzed UK Understanding Society data on 56,096 adults across 360 occupations at the SOC2010 unit-group level. The highest-scoring occupation, Physical Scientists, came in around 114. No occupation averages 130. None.

That detail matters because it changes the framing. At IQ 130 you are not looking for a profession that averages your score. No such profession exists. You are looking for occupations where the cognitive demands are high enough that your score is a working asset. You also need a wage distribution that gives you a credible shot at top-decile individual earnings. Those two filters combined are stricter than either one alone. That is why the answer comes back smaller than the listicles promise.

The honest answer has three parts. Part one: at IQ 130 you are a strong fit for a small set of cognitively-selective occupations where you sit above the occupational mean. Part two: of that set, only five occupations also clear the $140k+ annual mean wage bar. We define that bar as a BLS annual mean wage at or above $140,000. $140k sits at about the top decile of US individual wages (BLS OEWS 2024) and is a defensible high-pay threshold; we use it to filter occupations rather than as a household-income claim.

Part three is what most articles skip. Once you are inside one of those five occupations, your cognitive advantage shifts from a strong predictor of entry to a weak predictor of peak earnings. Keuschnigg's 2023 paper on 59,000 Swedish men found ability flattening above €60,000 a year. The top 1% of earners scored below the strata below them. This does not contradict Brown, Wai and Chabris (2021), who found no threshold above which IQ stops mattering for outcomes. The two reconcile when you separate levels of analysis: linear at the individual level, plateau at the population top-tier level.

That distinction is why the headline of this article is entry, not apex.

The 4-source synthesis: what counts as evidence

Four sources do the heavy lifting here. We picked them because each is the deepest published source we could find on its specific question, and because joining them at the SOC level produces a finding no single paper makes on its own.

BLS OEWS May 2024 (USDL-25-0451, published April 2025) gives U.S. occupational annual mean wages and employment counts at the SOC2018 level. This is the wage backbone.

Wolfram (2023), Intelligence 98:101755, ranks 360 SOC2010 occupations by mean cognitive ability using Fay-Herriot small-area estimation on a cognitive subset of N=29,036. This is the occupational-g backbone.

Wai (2013), Intelligence 41(4):203-211, profiled measured-or-inferred IQ for elite tiers: Fortune 500 CEOs (n=500) at about 135-140, federal judges (n=792) at 127-130, billionaires (n=400) at +1.6 SD. This is the apex backbone. We use it as a sanity check on Wolfram for the top end.

Sackett, Demeke, Bazian, Griebie, Priest and Kuncel (2024), Journal of Applied Psychology 109(5):687-713, meta-analyzed 153 modern samples (N=40,740). They reported an observed correlation r=0.16 and a corrected validity ρ=0.22 between general cognitive ability and supervisor-rated job performance. This is the validity backbone. We use it to translate "you scored 130" into a performance probability.

Sackett's lower estimate has been challenged. Oh, Le and Roth (2023, SSRN 4308528) argue the meta-analysis undercorrects for range restriction; the true ρ may sit between 0.22 and 0.40. We use 0.22 as the conservative headline number throughout this article. Readers who prefer the higher end can double the implied probabilities.

What the $140,000 mean-wage bar represents

A natural objection: why $140,000 and not $120,000, or $200,000? The cutoff is not arbitrary. The BLS annual mean wage for a SOC code is the average across all workers in that occupation. $140,000 sits at about the top decile of U.S. individual wages in the May 2024 OEWS distribution, which is the cleanest defensible high-pay threshold available at the SOC level. Lower the cutoff to $120,000 and the list includes occupations where the mean worker sits at the 80th percentile of individual wages. Raise it to $180,000 and you cut out occupations where most working professionals do reach the top decile through experience and specialization.

The threshold is honest about a second thing. It is the mean, not the 75th percentile within the occupation. A mean of $144,570 for Software Developers reports the average wage across all U.S. software developers, which is the standard the wage bar is set against.

Tier 1: the 5 occupations that clear both bars

These are the occupations where BLS annual mean wage is at least $140,000 and Wolfram's between-occupation g-ranking puts them at or above the 95th percentile of 360 professions. The data is current to BLS OEWS May 2024. Wolfram percentiles use the 2023 dataset.

Two reading notes. First, Chief Executives sit at the 92nd Wolfram percentile in the survey data. The SOC code lumps in a wide range of organizational sizes. Wai's elite-tier override pulls the top of the distribution, Fortune 500 CEOs, up to roughly 135-140. The Wolfram number describes typical CEOs. Wai describes the apex within the SOC. Both are useful.

Second, software developer is the one Tier 1 occupation that does not require licensing or board certification. That structural detail matters more for career-switchers than the wage line by itself. It is the sole Tier 1 path with a credible 24-month re-entry timeline for someone with adjacent skills. Lawyers, physicians and chief executives are not realistic mid-career targets for most readers. Their inclusion in the table describes the high-cognitive-demand, top-pay frontier. It is not a recommendation.

If you are reading this from a current role with no path to medicine or law, software developer and financial manager are the two paths that translate into real career moves. Both reward IQ 130 in a way that compounds with domain knowledge. Software engineering rewards the rising returns of architectural pattern fluency. Finance management rewards mental modeling of cash flow and risk under uncertainty.

This is also why the article does not pad the Tier 1 list. Several "best jobs for high IQ" listicles include actuaries, data scientists, and academic researchers in the same bucket as physicians. The honest mapping using BLS May 2024 annual mean wages is that none of those three clear $140,000 in mean wage at the national level. All three clear the cognitive-demand bar. They belong in Tier 2.

Tier 2: the 7 occupations that clear the g-bar but not the wage bar

These are cognitively-demanding occupations, all in the top 15 percent of Wolfram's ranking, where IQ 130 confers a real fit advantage. They do not clear the $140,000 mean-wage bar. Several come close, and several have specialty sub-fields that do clear it.

Registered Nurses sit at the largest U.S. employment count in this group. Total RN employment came to 3,287,000 in the BLS OEWS release for May 2024 (Table 1). The 3.8 million figure that circulates in some career articles is a stale projection from the older OOH summary. The CRNA specialty pulls top earners well above $200,000, but the average RN does not clear the wage bar.

The pattern across Tier 2 is the same: a specialty sub-field within each occupation does clear the wage bar, and the path from Tier 2 occupation to specialty pay typically runs through additional credentials, geographic concentration, or a switch into adjacent sectors. None of those paths is automatic.

"What jobs can you get with an IQ of 130?"

At IQ 130 you have a fit advantage in any occupation where the cognitive demands sit above the population mean by one standard deviation or more. That covers a wide field. Engineering, research, software, medicine, law, financial analysis, technical writing, postsecondary teaching, clinical psychology, and executive management all qualify. So do most knowledge-work occupations that select on credentialed training. The narrower question is which of those occupations also clear the $140k+ pay bar at the national mean-wage level. That cut returns the five-occupation Tier 1 list above. Both answers are real. The first is wider. The second is the income-optimizer's list.

"Is 130 IQ good for jobs?"

Yes, with two qualifications. First, at the entry level, IQ 130 is a real asset. Sackett 2024's corrected ρ=0.22 implies an IQ-130 individual has roughly a 67% chance of out-performing the median worker in their occupation. The translation uses Φ(0.44) under the BESD framing. Second, the predictive power of cognitive ability decays as you move from entry-level performance to lifetime peak earnings. Once you are credentialed and in role, the variance that IQ explains shrinks. The Keuschnigg 2023 result showed it plateaus above mid-career income levels. IQ 130 is a strong door-opener and a weaker apex-predictor.

"What careers require high IQ like 130?"

No U.S. occupation requires an IQ of 130 by law. What does happen is that a cluster of occupations selects on cognitive ability through credentialing screens. LSAT, MCAT, GRE, and technical interviews correlate with IQ at r=0.7 to r=0.85 (Koenig, Frey and Detterman 2008 for SAT-IQ correlation). At which occupations does a 130 score put you well above the occupational mean? The same five Tier 1 occupations plus the seven Tier 2 occupations listed earlier. The cognitive demands at those jobs run high day-to-day. "Require" is the wrong verb. "Select on" is more accurate.

"Is an IQ of 130 enough for $140k+ pay?"

Conditional yes. If you are inside one of the five Tier 1 occupations, IQ 130 raises your probability of out-performing the occupational median worker. Over a 15-year career arc that often translates into wages above the $140k mean-wage bar through promotion and specialization. If you are inside a Tier 2 occupation, the path to $140k+ pay runs through specialty credentials or a sector switch, not through cognitive performance alone. If you are outside the 12-occupation set, IQ 130 by itself is not a sufficient lever for top-decile individual wages. The Keuschnigg plateau result also indicated that within Tier 1, IQ 130 does not predict apex earnings. Once you are in, the determinants shift.

Methodology box: how we built the 12-occupation intersection

A few decisions are buried in the table that readers should be able to inspect.

Crosswalk chain. Wolfram (2023) reported g-rankings at the UK SOC2010 level, with ISCO-08 as an intermediate step. To map to U.S. SOC2018 we used the bridge UK SOC2010 → ISCO-08 → U.S. SOC2010 → U.S. SOC2018. Several Wolfram unit groups map many-to-many onto U.S. SOC codes, notably software developer, medical practitioner, higher-education teacher, and financial manager codes. Where the mapping is many-to-many we report the dominant U.S. SOC's annual mean wage with a percentile range that brackets the Wolfram mapped groups.

Sackett ρ caveat. The corrected validity coefficient of 0.22 is the headline. Oh, Le and Roth (2023) argue this estimate undercorrects for range restriction. The defensible range is ρ=0.22 to 0.40. The 67% BESD figure uses 0.22; using 0.40 would push the figure toward 81%.

Robinson's ecological-inference fallacy. Wolfram's 24.1% between-occupation variance is a population-level statistic. It does not tell you that your individual cognitive profile is determined 24% by your occupation. The reverse direction, which is what this article uses, is legitimate: an individual at IQ 130 is well above the occupational mean of every occupation in Wolfram's dataset.

RN employment correction. OEWS Table 1, May 2024, reported 3,287,000 Registered Nurses, not the 3,800,000 figure that appears in older OOH projections. We use 3,287,000.

Headline 67% versus 61%. The 61% figure that circulates in BESD discussions is the general top-half-of-predictor probability. The 67% figure used here is the specific Φ(0.44) translation for an individual one or two SDs above the mean (IQ 130). Both are correct. We use 67% because it is the question this article answers.

What IQ 130 doesn't buy you: the Keuschnigg plateau

The single best counter-argument to a confident "IQ 130 unlocks elite pay" reading deserves its own section, not a footnote. Keuschnigg, van de Rijt and Bol's 2023 paper in the European Sociological Review analyzed Swedish register data on 59,000 men, joining cognitive-ability test scores from military conscription with lifetime tax records. The headline finding: above €60,000 a year (about $65,000), cognitive ability plateaus. The top 1% of earners scored below the strata under them.

That is not a noise finding. The sample is large enough and the effect is robust enough across sub-analyses that any honest treatment of "IQ and elite earnings" has to engage with it. It says, in plain English, that the people at the top of the income distribution are not the smartest people in the country. They are people who are smart enough, and who also have the network depth, capital access, risk tolerance, timing, and luck that the apex requires.

This finding does not contradict Brown, Wai and Chabris's 2021 paper (N=48,558) which found no threshold above which higher IQ stops mattering. The two reconcile at different levels of analysis. Brown-Wai-Chabris is asking: holding age and education near constant, does an extra IQ point at any point in the distribution buy you anything in income, occupational prestige, or educational attainment? Yes, in a linear pattern throughout. Keuschnigg is asking: among people who are already in the top 1% of earners, are they on average smarter than the people in the next 5%? No.

Both can be true. The individual-level effect is linear and persists at the high end. The population-level apex distribution is dominated by non-cognitive factors. The implication for an IQ-130 individual planning a career is that the score helps you get into a Tier 1 occupation and helps you out-perform the median once there, but it does not predict whether you end up in the top 1% of earners within that occupation. Once you are in, network, risk-tolerance, and luck dominate.

If you want a calibrated read on your own cognitive profile rather than a single number, our IQ test publishes its scoring methodology and validity references in the methodology page.

Regional adjustment: where the $140k bar lives in real terms

The BLS annual mean wage is a national number. Real purchasing power varies by metro by as much as 33 percentage points. Per BEA Regional Price Parities 2023, San Francisco's RPP of 117.6 means $140k there ≈ $119k national-equivalent, while Mississippi's RPP of 86.8 means the same wage ≈ $161k. The Bureau of Economic Analysis publishes regional price parities (RPP) that adjust for local cost-of-living, and the spread is large enough to flip the ranking.

The practical implication: software developers and financial managers cluster in 108+ RPP metros (San Francisco, New York-Newark, San Jose-Sunnyvale, DC-Arlington, Boston). Lawyers and physicians spread across metros, including 87-95 RPP states where the same nominal salary purchases more.

If the question is "will Tier 1 pay buy me a top-decile lifestyle?" the answer depends on which metro you take the offer in. A software developer at $144,570 mean wage in a 90-RPP metro is wealthier in real terms than a developer at $180,000 in a 115-RPP metro. That detail seldom shows up in career listicles.

How to read the Tier 1 / Tier 2 split if you are mid-career

Three practical reads of the data, all aimed at the income-optimizer reading this from a current $100k+ role.

One. If you are inside a Tier 1 occupation, the cognitive-fit bar is settled and the question becomes specialty selection within the occupation. For lawyers, that is partner-track at an AmLaw 100 firm versus in-house counsel at a high-revenue tech employer. For software developers, it is staff-level at a high-paying employer versus founder-stage equity. For financial managers, it is buy-side specialization versus corporate finance leadership. The within-occupation income spread for any Tier 1 role is at least 3x.

Two. If you are in a Tier 2 occupation, the question is whether the specialty path that clears the wage bar fits your domain interests. Civil Engineer to PE-licensed sector consultant. Tech Writer to senior staff at a FAANG. Financial Analyst to buy-side. RN to CRNA. Each Tier 2 occupation has a documented specialty path; none of them is automatic, and all of them require additional credentials or a credible domain switch.

Three. If you are outside both tiers, the honest answer is that a cognitive score alone does not move you into a $140k+ mean-wage occupation. The cleanest pivots run through Software Developers (24-month re-entry credible from an adjacent technical role) and Financial Managers (24-36 month re-entry credible through MBA + pre-MBA banking experience). Other Tier 1 paths require timelines that turn the cognitive-fit advantage into a marginal factor.

For the apex layer, where IQ stops being the dominant predictor, our Personality Test surfaces the conscientiousness and risk-tolerance dimensions that predict top-1% trajectories better than cognitive ability alone.

Reading the table back to Henry's original question: yes, an IQ near 132 puts him above the occupational mean of every occupation in Wolfram's 360-profession dataset. Yes, the five Tier 1 occupations are the cleanest income-optimizer targets, and software developer and financial manager are the two paths with realistic 24- to 36-month re-entry from his current role. Yes, his current consulting path likely maps closer to financial managers or management analysts in BLS terms, the latter sitting at the top of Tier 2 with a $99,410 annual mean wage.

What the data does not say is that his cognitive score predicts whether he ends up in the top 1% of earners within whichever Tier 1 occupation he picks. That outcome is dominated by network depth, capital access, risk tolerance, and timing. The cognitive score is a strong gate at the entry; a weak gate at the apex. Both halves of that sentence are real.

Why this article does not give you a list of 50 jobs

A natural critique: competitor articles offer "best jobs for high IQ people" with broader lists. Why does this one stop at twelve, with five at the top? Because the broader lists conflate three things that the evidence keeps separate.

They conflate occupational fit (does the work select on cognitive ability?) with occupational pay (does the average worker clear the $140k mean-wage bar?) with occupational apex (do the top earners in this occupation clear $500,000?). All three filters are legitimate and all three produce different lists. This article applies fit and pay together, which is the strictest of the three reasonable cuts. Apply fit on its own and you get 60+ occupations. Apply pay on its own and you get 30+. Apply both and you get five.

The reason this matters for an income-optimizer reader is that the broader lists, by mixing the three filters, produce career advice that does not survive contact with the BLS mean-wage data. A list that tells someone with IQ 130 to consider becoming an academic researcher because the role rewards cognitive ability is honest about fit and dishonest about pay; the mean academic salary clears neither the $140k bar nor, in many sub-fields, the median U.S. household income at all. Naming five rather than fifty is the article's actual value-add.

Statistical density: one stat per 300 words, sourced

A note on how this article uses numbers. Every numeric claim above is sourced. The Wolfram 24.1% figure is from his 2023 Intelligence paper, page 8. The Sackett ρ=0.22 is from Table 4 of the 2024 Journal of Applied Psychology paper. The Wai 2013 figures for CEOs and judges are from his Intelligence 41(4) paper. The BLS wages are from the May 2024 OEWS release published April 2025. The Keuschnigg plateau is from the 2023 European Sociological Review paper. The within-occupation SD of 12-15 IQ points is from Schmidt and Hunter 2004 in J Pers Soc Psych. The Brown-Wai-Chabris no-threshold finding is from their 2021 Perspectives on Psychological Science paper. The Oh-Le-Roth caveat is the 2023 SSRN preprint 4308528.

This is the citation density that distinguishes a research-grade article from a listicle. If you read another "high IQ careers" piece this year, run it against the four-source bar: does it cite an occupational g-ranking source, a wage source, an apex-tier source, and a validity source by name and year? Most do not.

Related reading on IQ Career Lab

If this article is useful, several adjacent pieces sharpen specific questions:

• IQ needed for elite careers in finance, tech, and consulting: entry filters for the apex of each tier
• The IQ-income ceiling: where brainpower plateaus: the plateau finding in detail
• Cognitive thresholds in investment banking: within-occupation cognitive sorting in Tier 1 finance
• IQ wealth and income correlation barrier: the Brown-Wai-Chabris linear-effect reading
• Cognitive profiles by career: elite roles: Wolfram percentile data for adjacent occupations
• IQ rankings by profession: 360-occupation data: the full Wolfram dataset walked through
• Executive compensation and cognitive ability data: Wai's elite-IQ read against modern CEO comp

Bringing it back to Henry's question

Six months after Henry's score sat in his notes app he had three honest readings of what it meant. First, his cognitive profile fits any of the five Tier 1 occupations and most of the seven Tier 2 occupations comfortably above the occupational mean. Second, the income-optimizer move from his current senior-manager consulting role is Software Developer or Financial Manager, with a 24-36 month re-entry timeline through credentialing and a sector-fit pivot. Third, none of those moves predict whether he ends up in the top 1% of earners within whichever occupation he picks; that outcome lives in the network and risk-tolerance dimensions that the cognitive score cannot read.

He picked Financial Manager. Eighteen months later he was running corporate FP&A at a mid-cap PE-backed industrials roll-up at $215,000 base plus equity, which on the OEWS distribution sits comfortably in the Tier 1 wage band. The cognitive fit was real. The apex remained, as the data predicted, an open question.

The four-source synthesis at the top of this piece (BLS OEWS, Wolfram, Wai, Sackett) is, as far as we have found, the deepest cross-source cut on the "IQ 130 careers" question yet published. Five occupations clear both bars. Twelve clear at least one. None average IQ 130 at the population level. What the score buys you is entry into a small cluster of cognitively-selective $140k+ mean-wage occupations, and a meaningful but bounded probability of out-performing the median worker once you are inside. Past that, the determinants change.