Job Market TrendsEntry-Level Job Requirements: Soft Skills Beat Technical Ones 3 to 1
JobLeads analyzed 1.2 million entry-level job listings to find what skills employers request most. Learn what entry-level jobs actually require, pay, and offer.

The gender pay gap is more complicated than a single number.
Women enter the job market expecting less, applying less, and concentrating in lower-paying industries. They also accept more flexibility trade-offs and gravitate toward roles with a different skill profile.
Hence–
The wage gap is the product of all of these factors combined.
This study draws on behavioral data from 881,776 JobLeads users in the United States, tracking how men and women search, browse, and apply for jobs. The result is not a single number but a map of where and how exactly the gender pay gap is built.
Key findings:

The gender pay gap starts even before the actual job search.
Before a woman sends a single application, she has already set her salary expectation. And on average, that expectation is lower than a man's. This is the first form of wage inequality.
The broader picture confirms this is not a new problem. In 2023, an AAUW study found that women working full-time year-round earned just 83% of the median salary paid to men ($55,240 compared to $66,790). And at the hourly level, EPI shows that women were paid 18% less than men in 2024. The good news is that even though the gap is substantial, this is the lowest recorded gap in history.
JobLeads' gender pay gap analysis shows women's average low salary expectations standing at $72,282 versus men's at $79,906, which is a 9.5% gap. The high-end average follows a similar pattern. Women expect $156,846 versus $170,842 for men, an 8% difference.

Roughly 30% of women and 31% of men browse jobs above their stated salary ceiling which is a near-identical reach rate. But when women do stretch beyond their range, the jobs they look at pay on average $11,293 more than the ones men browse.
Women aren't more conservative in their aspirations, they're more conservative in what they believe they're already worth. This is what the wage gap between men and women looks like before a single application is filed. Academic research confirms the pattern. A large-scale Kiessling et al. study of over 15,000 students found a significant gender gap in wage expectations before labor market entry that mirrors actual wage differences across the entire salary distribution.
Zooming out on the long-run trend. In 2024, Pew Research Center found that women earned an average of 85% of what men earned, up from 81% in 2003 and 65% in 1982. Progress is real, but slow. At this pace, AAUW projects pay equality won't arrive until 2088.
Looking at different industries, the expectation gap isn't evenly distributed and the direction of the gap varies significantly by sector.
| Industry | Female Median Ceiling | Male Median Ceiling | Female Median Job Salary | Male Median Job Salary | Female Excess | Male Excess |
|---|---|---|---|---|---|---|
| Consulting | $98,751 | $98,751 | $132,227 | $146,813 | $33,476 | $48,062 |
| Management & Operations | $79,001 | $123,439 | $127,318 | $160,999 | $48,317 | $37,560 |
| Finance | $79,001 | $98,751 | $124,521 | $149,424 | $45,520 | $50,673 |
| IT & Technology | $79,001 | $98,751 | $123,821 | $147,162 | $44,820 | $48,411 |
| Legal | $79,001 | $79,001 | $123,814 | $138,113 | $44,813 | $59,112 |
| Marketing & Media | $79,001 | $98,751 | $119,104 | $126,667 | $40,103 | $27,916 |
| Engineering | $79,001 | $79,001 | $103,585 | $118,511 | $24,584 | $39,510 |
| Human Resources | $79,001 | $79,001 | $110,597 | $117,514 | $31,596 | $38,513 |
| Sales | $79,001 | $98,751 | $107,535 | $130,385 | $28,534 | $31,634 |
| Bio & Pharmacology & Health | $79,001 | $98,751 | $107,895 | $124,560 | $28,894 | $25,809 |
Gender pay gap reporting rarely drills below the industry level. In Legal, male users browsing jobs above their salary ceiling are targeting significantly higher-paying roles ($59,112 higher than their expectations) than their female counterparts ($44,813 higher than their expectations). This is the largest male-skewed gap in the dataset.
A similar pattern holds in Consulting, Finance, and IT, where men consistently stretch further above their ceiling than women. This suggests they are targeting more senior or higher-band roles within these higher-paying industries.
However, other sectors tell the opposite story. For example, in Management & Operations, women search jobs with a salary higher than their expectations by $48,317 outpaces men's $37,560. This is despite women in this sector having a notably lower salary ceiling ($79k versus $123k) which means they are browsing similarly-priced jobs from a much lower starting point. Marketing & Media follows the same pattern, with female users stretching further above their ceiling ($40,103 versus $27,916 for men).
Engineering presents a more nuanced picture: women browse more aspirationally in terms of reach rate–interacting with above-ceiling jobs at a rate 4.9 percentage points higher than men–but the roles they engage with carry a lower average excess ($25k versus $40k for men). Women in Engineering are reaching more often, but into moderately-paying roles rather than the highest-band positions.
These statistics suggest the pay gap between men and women begins in the mind, and the market follows.
Women browse as much as men. JobLeads' data shows that average clicks on a job listing per user are virtually identical. The gender gap isn't in who's showing up to look, rather it's in who decides to apply.

As many as 94% of men who clicked on at least one job also submitted at least one application, compared to 81% of women.
Beyond the volume gap, there's a salary gap embedded in the choices themselves. Women apply to jobs with a $12,667 lower median salary than men (a 15% gap). This isn't what's offered to them or what they expect; it's the actual roles they select.

And notably, this gap is wider than the 11% gap observed across all job interactions in our dataset, meaning the act of applying amplifies it. Women are more selective when they commit, and that selectivity skews toward lower-paying roles relative to what they browse.
This behavioral pattern at the apply button connects to a well-documented dynamic in salary negotiations. A ResumeBuilder survey found that only 32% of women had negotiated their pay in the past two years, compared to 49% of men, making women roughly one-third less likely to negotiate.
And even when women do push back, they're less successful: only 42% of women who negotiated got what they asked for, versus 55% of men. Pew Research confirms a related pattern where women are significantly more likely than men to report discomfort when asking for higher pay, and are more likely to face rejection when they do. The friction starts earlier in the process, but it compounds at every stage.

The gap in application rates is largest precisely in the fields where women are already the minority. For example, IT & Technology shows a nearly 36% higher application gap where women browse tech roles nearly as much as men, but apply at dramatically lower rates.
The only industry with near-parity is Bio & Pharmacology & Health, the sector where women are already the majority (72.5% of users who work in the industry). The friction at the apply button appears to be amplified when women are navigating spaces where they're already underrepresented.
Consulting and Engineering have the lowest female application rates of all, both below 50%. These are industries where the male majority structure may be doing some of the discouraging before the job description even finishes loading.
And this isn't just about applying. It's also connected to negotiations. Research by Kennedy, Kray & Lee shows that women from a top business school actually reported negotiating salary more often than men (54% vs 44%). The problem is that they are more frequently rejected. Kiessling et al confirmed that women plan to act less boldly in wage negotiations, accounting for between 14 and 15% of the gender gap in expected starting wages.
One of the most persistent drivers of the gender wage gap is occupational segregation. Even before the application and expectation gaps take hold, there's a more fundamental divide: men and women are largely operating in different corners of the job market.
Bio & Pharmacology and Human Resources are female-dominated, with women making up over 70% of employees in each. Engineering and IT are the mirror image where men account for 65-76% of job interactions. These map almost perfectly onto salary outcomes.

The most important insight in this data isn't the most predictable one. Legal is a female-majority industry (62% of workers are women) yet it carries the largest median salary gap in the entire dataset of +26% in favor of men.
Is the gender pay gap real within industries, not just across them? For Legal, the answer is definitely yes. Being the majority in an industry is no guarantee of equal pay for women within it. The gap in Legal isn't about who's there; it's about which roles each gender occupies inside it.
The omen wage gap for the Legal sector is $125,399 versus $141,506 for men, which is a $16,107 disadvantage. This shows that even when both genders are present in the same industry, women still receive lower pay.
| Industry | Female Median | Male Median | Median Gap |
|---|---|---|---|
| Consulting | $102,593 | $107,895 | +5.2% M |
| Sales | $79,241 | $88,348 | +11.5% M |
| Finance | $88,876 | $105,842 | +19.1% M |
| IT & Technology | $93,744 | $101,951 | +8.8% M |
| Legal | $90,309 | $113,663 | +25.8% M |
| Management & Operations | $91,443 | $107,895 | +18.0% M |
| Engineering | $86,674 | $88,348 | +1.9% M |
| Marketing & Media | $87,099 | $91,976 | +5.6% M |
| Human Resources | $82,495 | $84,906 | +2.9% M |
| Bio & Pharmacology & Health | $79,495 | $85,577 | +7.6% M |
Meanwhile, the industries with the narrowest salary gaps include Engineering (+2%), HR (+3%), and Marketing & Media (+6%). They're also the ones where application behavior by salary band is most equal. In these sectors, the playing field appears more level across multiple dimensions simultaneously.
BLS figures show that in 2023, women full-time workers' median weekly earnings were 84% of men's. Moreover, Pew Research found that even as women today are more likely than men to hold college degrees, the gender pay gap between college-educated men and women is no narrower than for those without degrees.
Why is there a gender pay gap? One underexamined answer is the flexibility tax. Women disproportionately seek flexibility in their work arrangements and that flexibility comes with a price.

In fact, 37% of women on JobLeads seek remote roles, versus 30.5% of men. On top of that, women are 55% more likely to browse part-time jobs (23% vs 15%). These aren't choices made in a vacuum. External research consistently links these preferences to caregiving responsibilities that still fall disproportionately on women.
The scale of the motherhood penalty is striking. A 2025 analysis of Census Bureau data found that full-time working mothers earned 35% less than full-time working fathers in 2024. And there is no equivalent penalty for men. Full-time fathers of children under 18 actually earn roughly 25% more than childless male full-time workers, which is sometimes known as the "fatherhood bonus." On the flip side, unmarried childless women earn 93 cents on a childless man's dollar.
The Pew Research Center shows that even when women outearned their husbands, they still took on more household and caregiving work. Women were twice as likely as men to work part-time in 2023, often due to caregiving responsibilities.
What makes this finding particularly sharp is where the salary penalty lands. Remote work, the setting women gravitate toward most, shows a 10.6% male salary premium. On-site roles show a 9% premium. The pay gap between men and women doesn't disappear when women choose flexibility.
The part-time data adds an interesting counterpoint to the women's pay gap narrative. The part-time jobs women browse actually pay more than those men browse ($94,307 versus $85,618). This is explained by industry composition as women's part-time browsing spans professional sectors like Bio & Pharma, Management, and HR. Men's part-time browsing concentrates in IT and Engineering, where flexible contracts tend toward junior or contract work.
But there's an even harder ceiling that emerges at the top. Women outnumber men at every part-time seniority level up through the Head of Department. At Managing Director and above, the ratio flips and men account for 56-67% of senior part-time job interactions. Fewer senior part-time roles appear to exist for women, or women self-select away from them, knowing the trade-off becomes more extreme at the top.
Why are women paid less, even within the same industry? It's connected to specific roles men and women gravitate toward differ in their skill composition.

Jobs women interact with require 31% soft skills on average, versus 25.5% for men, which is a 5 percentage point gap. Jobs men apply for average 0.44 more technical skills per posting. The pattern holds across every single industry without exception.
This matters because the market prices these skill types differently. That 5pp soft skill differential correlates directly with an $9,650 median salary gap, as jobs requiring more interpersonal and organizational skills post lower salaries across the board.
It's not a coincidence; it's how the market has historically valued these skills relative to technical ones. The academic evidence for this is robust–for example, a landmark study by Levanon, England, and Allison using five decades of U.S. Census data found substantial evidence for the devaluation view. That means as more women enter a job sector, pay in that occupation falls, even after controlling for education and skill requirements.
The wage drop follows women, not the other way around. When asking what is the wage gap in terms of root causes, skill devaluation is a significant and underreported answer. Gender wage gap statistics that focus only on industry miss this intra-industry dimension entirely.
Women vs men gravitating towards positions that require predominantly soft skills
| Industry | Female % Soft | Male % Soft | Female Med Salary | Male Med Salary | Salary Gap |
|---|---|---|---|---|---|
| Human Resources | 35.5% | 33.3% | $82,495 | $84,906 | +2.9% M |
| Legal | 34.6% | 32.6% | $90,309 | $113,663 | +25.8% M |
| Finance | 31.5% | 29.5% | $88,876 | $105,842 | +19.1% M |
| Management & Operations | 32.8% | 31.2% | $91,443 | $107,895 | +18.0% M |
| Bio & Pharmacology & Health | 31.3% | 29.8% | $79,495 | $85,577 | +7.6% M |
| Sales | 30.8% | 30.5% | $79,241 | $88,348 | +11.5% M |
| Marketing & Media | 29.5% | 27.0% | $87,099 | $91,976 | +5.6% M |
| Consulting | 27.8% | 23.9% | $102,593 | $107,895 | +5.2% M |
| Engineering | 25.2% | 22.6% | $86,674 | $88,348 | +1.9% M |
| IT & Technology | 21.3% | 15.0% | $93,744 | $101,951 | +8.8% M |
In IT & Technology, women's jobs carry the largest soft skill gap of any sector (+6pp). The roles women are drawn to within tech lean more heavily on interpersonal skills, and this connects directly to both lower pay and lower application conversion rate. This is also one reason the gender pay gap in tech is so persistent. It's not just that women are underrepresented, it's that the roles they do occupy are valued differently.
In Legal, women's roles require more soft skills (+2pp) and pay $23,354 less at the median. Men and women are in the same sector but in structurally different roles, with a structurally different compensation. Measuring the gender pay gap accurately means accounting for this kind of within-sector skill variation. This is often missed by aggregate wage statistics.
As Levanon et al. put it, the devaluation effect means that the pay penalty doesn't require individual discrimination. Instead, it's baked into how markets price the work that women predominantly do.
Fixing the pay gap requires intervention at every stage, not just the paycheck.
The gender wage gap is often framed as a single number which is a percentage difference in annual earnings that could, in theory, be closed by a single policy lever. But the data in this study shows the gap is built across five distinct stages. These include salary expectations, job applications, industry sorting, flexibility trade-offs, and the skill composition of the roles women actually occupy.
Each of these gaps compounds the others. In Sales, women are browsing jobs that pay far above their stated expectations, suggesting the expectation gap is suppressing ambition in a sector where the market is willing to pay more. Moreover, in Engineering, women are reaching above their salary ceiling more often than men, but into moderately-paying roles rather than the highest bands.
Closing the pay gap means intervening at every one of those stages. Salary transparency helps narrow the expectation gaps. Women are more likely to apply when it's made explicit that salary negotiation is on the table. Also, the market's undervaluation of soft skills relative to technical ones needs to be actively challenged, not accepted as neutral.
Equal pay cannot be achieved at the paycheck alone. That is the last place the gap appears, not the first.
This analysis is based on behavioral data from the JobLeads platform, covering October to December 2025 (Q4 2025).
The total sample comprised 881,776 users in the United States, of whom 433,122 were identified as female and 448,654 as male. These figures reflect the sample after applying a gender prediction filter. Users whose gender could not be assigned with sufficient confidence were excluded.
Gender was not self-reported by users. Instead, it was inferred using probabilistic name-gender mapping, which is a method that assigns a predicted gender based on each user's first name.
The analysis was not filtered by contract type (80% full-time, 20% part-time). A separate check confirmed the gender pay gap persists across both contract types, including a +2.5% male premium in part-time roles where women apply at twice the rate of men.
The analysis tracks five dimensions of job search behavior, each corresponding to a section of this article:
Limitations:
If our research helped you better understand gender pay gaps in the US, feel free to share any insights or statistics from this study. Please remember to credit JobLeads as the source and include a link back to this page. Thank you!
Content & Insight Writer
Beata creates content that puts job seekers first. From practical blog advice to first-hand research studies, her writing is designed to give people the clarity and confidence to find the role they deserve.
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