Key points:
- Between 2022 and 2024, about 2.6% of Indeed users switched to new jobs every month, and 64% of those job switchers also changed occupations.
- Nursing and software development have the lowest proportion of job-to-job movers coming from another occupation. These are also the occupations that people are most likely to stay in when they switch jobs.
- Hospitality, arts & entertainment, childcare, logistic support, and personal care & home health are the occupations people are most likely to leave when they switch jobs.
- Attrition rates tend to be higher in occupations with weaker labor demand and lower salaries.
For more information, check out our companion piece to this analysis, with interactive diagrams and downloadable charts.
Every month, about one-in-forty Indeed users with an uploaded resume switches into a new job, and almost two-thirds of them switch to a new occupational category, according to a Hiring Lab analysis of tens of millions of U.S. Indeed user profiles.
Job-to-job moves account for most new hires and play a crucial role in reallocating talent to where it’s most needed, and the rate at which workers move between jobs can tell us a lot about the labor market. High levels of inflows resulting from job-to-job transitions, both within and across occupational lines, can indicate strong hiring activity and economic momentum, high demand, and/or low barriers to mobility within certain job categories. And in some cases, high turnover may be driven by lower job security and short job durations.
This analysis examines post-pandemic job mobility patterns by leveraging Indeed’s unique database of anonymized jobseeker profiles. Using more than 35 million Indeed profiles in the United States, we tracked job-to-job moves between 2022 and 2024 to determine which occupations have the highest job switching rates, and which ones people are most and least likely to leave when they change jobs. This large sample is particularly well-suited to analyzing worker mobility and career dynamics by providing granular occupational detail and records of employment transitions, complementing more static sources of job transition data.
On the move: Occupations with the highest and lowest job switching rates
Between 2022 and 2024, about 2.6% of Indeed users switched into a new job every month — a number that lines up with other employment transition data. But some jobs see a lot more movement than others.
For example, jobs in loading & stocking had the highest rate of job switchers, with about 1 in 30 positions filled each month by someone coming from another job (either from within loading & stocking or from another occupation). In contrast, media & communications roles were more stable, with just 1 in 60 jobs filled that way.
Lower-paying fields like retail, loading & stocking, and food preparation & service see higher job switching rates of more than 3% each month. Jobs in media & communications, beauty & wellness, arts & entertainment, and management tend to have more stability. On average, fewer than 1.8% of workers in these fields switched into a new job each month.
Hard to enter: Nursing and software development are almost closed circuits
Overall, occupational mobility among job switchers is high. Almost two-thirds (64%) of those moving into a new job from another changed occupations. However, this ratio varies greatly for individual job categories. Nursing and software development are especially closed off to job switchers from other occupations. Most people switching into a nursing job (66%) previously worked in nursing, and the same holds true for software development (55%). On average, job switches from another occupation account for fewer than 1% of jobs in these categories each month.
Other occupations are comparatively open to incoming job switchers from different fields. In hospitality & tourism, retail, and loading & stocking, the share of workers coming in from another occupation each month exceeds 2.2%. Most people switching into new jobs in these categories have previously worked in a different occupational category, including 88% of people switching into jobs in hospitality & tourism, around 74% in retail, and 69% in loading & stocking. In other words, these occupations rely more heavily on external talent pools to fill monthly vacancies, likely attributable to higher worker turnover and workforce attrition.
Overall, the share of jobs resulting from a switch from a different occupation tends to be particularly low in occupations requiring formal credentials, occupational licenses, and/or highly specialized skills. Examples include healthcare-related jobs (including nursing, dental, physicians and surgeons, and pharmacy) or regulated white-collar jobs, including accounting and legal occupations. Professional standards and qualification requirements tend to restrict the mobility of workers towards these fields.
Occupations workers are most and least likely to leave
Job categories differ not only in how easily they attract candidates from other fields, but also in how commonly workers who leave a job in a given occupation move on to other occupations. We calculated an exit rate for each occupation as the share of people who originally had a job in that occupation and switched to another one when they changed jobs.
The occupations that people are most likely to leave when taking on a new job are hospitality & tourism, arts & entertainment, childcare, logistic support, and personal care & home health. Each of these categories has an exit rate of more than 80%. At the high end, 91% of Indeed users who moved to another job and whose profile recorded the end of a work experience in hospitality & tourism, switched to a different occupation altogether. A look at the top job titles in each category highlights substantial variation within job categories. For example, within hospitality & tourism, 98% of park attendants who directly moved into new jobs from 2022 to 2024 left hospitality altogether, compared to only 66% of casino dealers.
Occupations with the lowest share of job switchers who moved to different fields included accounting, where about half of job switchers stayed within the same occupation, followed by therapy, dental occupations, software development, and nursing. Fewer than one in three nursing professionals moved to another job category when switching jobs. Yet, even within nursing, the variation is considerable: Four in five former chief nursing officers left for another occupational category, while 93% of former family nurse practitioners stayed in nursing when switching jobs.
Curious where these job switchers end up after leaving their previous field? We trace the flows in and out of Indeed’s occupational categories here.
Occupations with younger workforces, lower demand, and lower wages tend to have higher exit rates
Career moves across roles, sectors, or occupations can reflect a wide range of motivations. Sometimes it’s by choice, sometimes out of necessity, especially when worker demand is low. In fact, occupations with more job opportunities — those with a higher average Indeed Job Posting Index (JPI) value — tended to see a slightly lower share of job switchers leaving for other occupations; underlining that when workers feel secure and see future prospects within their current occupation, they’re more likely to stay. On the other hand, limited growth opportunities or job insecurity can act as a push factor, prompting individuals to explore other occupational paths. The data shows that workers in occupations requiring highly specialized skills, including many medical and STEM-related fields in high demand in recent years, are somewhat less inclined to leave their current career paths.
Switching jobs can also serve as a stepping stone to better employment opportunities: Research shows that job switching is often associated with a pay bump (also known as the wage ladder). Unsurprisingly, better pay is a key motivator for many who decide to move on. Our data backs this up: Workers in occupations with lower average posted salaries were more likely to switch into a different occupational category. It suggests that when wages lag, mobility rises — a sign that many workers are actively seeking better prospects.
The average career length in an occupation — a proxy for the age of its workforce — also affects the likelihood of job switchers exiting that occupation. “Younger” job categories tend to have less occupational licensing or shorter training and education periods, attracting career starters who may not have much work experience, or are financing their education through jobs. Lower barriers to entry may bring in more transient workers, including students or career starters, reducing the likelihood of sustained commitment to the field. Occupations employing workers with longer average careers are more likely to require specialized training and qualifications, and the lower leave rate in these cases is also a result of higher investment in education or training. For example, the typical career length in a childcare role before a worker switches is just 4 1/2 years, after which about 86% of job switchers move to a new occupation. The typical pre-switch career length for an accountant is slightly under 10 years, with just 52% switching into a new occupation after that period.
Conclusion
This analysis shows significant variation in job mobility across occupational categories, and these differing mobility patterns have real implications for the job market and broader economy. For job seekers, high-turnover occupations may offer easier entry points — especially for those early in their careers or seeking reorientation — but may also provide less long-term stability or wage progression. Conversely, more stable occupations may demand higher initial investment in training but offer better retention and more evident progression once inside.
For employers, these patterns point to different strategic needs. Those in high-mobility occupations may need to focus on attraction and onboarding, while those in low-mobility occupations may benefit more from internal development and retention strategies. Recognizing whether a given job category is more “open” or “closed” helps both employers and workers navigate the frictions and opportunities inherent in job switching.
Methodology
We identify job switches based on the start and end dates of work experiences communicated on individual resumes. We limit our analysis to profiles in which the job start and end dates include the year and the month, rather than only the year. We focus on the 2022–2024 post-pandemic period. The resulting dataset contains more than 35 million anonymized user resumes on Indeed in the United States.
A job switch is any job start preceded by another work experience. We define the job switch rate as the ratio of the number of job experiences starting in month t that were preceded by other job experiences on the resume, divided by the total number of job experiences in the dataset that include month t. The occupation switch rate is calculated as the ratio of the number of job experiences starting in month t, with previous experience in a different occupation, divided by the total number of job experiences in the dataset that include month t.
The occupational exit rate among job switchers is calculated as the ratio of the number of experiences in category i, which are followed by a job experience in a different category during period t, divided by the total number of experiences in category i that precede a job experience in period t. The calculation is based on switches from one stable job to another (>6 months tenure in both jobs) to avoid capturing seasonal jobs or internships, with a maximum gap of 6 months in between.
Median career length is defined as the number of months between the start of a person’s first work experience and the end of their most recent work experience listed on their resume. It is based on all profiles of those who switched jobs in the years 2022-2024, under the same stability conditions listed above.
If the occupational exit rates of job switchers appear high, there are a few important caveats to remember. First, since Indeed is a job matching platform, individuals in long-term, stable employment relationships who don’t actively search for jobs are less likely to be represented in our data. Second, resume-writing conventions may differ across occupations and job types, affecting how experiences are reported. For instance, self-employment and freelance work may be reported by summarizing multiple short-term engagements under a single, continuous role, only distinguishing a new experience if it represents a significant shift. Third, some occupational categories — such as management or administrative assistance — are more likely to attract talent from a broad range of occupations. This can inflate apparent switching rates into and out of those roles.
