Income Percentiles by Occupation and Education Level

Postal Service Mail Sorters, Processors, and Processing Machine Operators

Total Income to Compare: $

Income Percentile Results

Total Income of $55,000 ranks between the 49.9th and 78.9th percentiles for all education levels. These results were estimated off of 65,351 Postal Service Mail Sorters, Processors, and Processing Machine Operators.

50th Percentile (Median) Income for any Education Level: $55,000
75th Percentile: $62,300
95th Percentile: $86,801
99th Percentile: $105,082

See Similar Occupations

Income Percentile Stats

  • To be in the top 1% for this age range, your household would need an income of $105,082 per year. This would include salary, investments, and any business income.
  • To be in the top 5% for this age range, your household would need an income of $86,801 per year. This would include salary, investments, and any business income.

Income of Postal Service Mail Sorters, Processors, and Processing Machine Operators by Highest Education Level

Total Income of $55,000 ranks for education levels:
  • Compared to Doctoral degree holders this ranks between the 24.3th and 24.3th percentiles.
  • Compared to Professional degree beyond a Bachelor's degree holders this ranks between the 31.6th and 100th percentiles.
  • Compared to Master's degree holders this ranks between the 50.4th and 74.9th percentiles.
  • Compared to Bachelor's degree holders this ranks between the 41.3th and 74.5th percentiles.
  • Compared to HS Diploma / GED degree holders this ranks between the 52th and 82.1th percentiles.

Income Percentile Distribution by Education Level

Highest Level of Education for Postal Service Mail Sorters, Processors, and Processing Machine Operators:
  • Other (N/A or Less than HS): 3.8%
  • HS Diploma / GED: 31.9%
  • Associates Degree and Some College: 47.9%
  • Bachelors Degree: 13.8%
  • Masters Degree: 2.4%
  • Professional Degree beyond a Bachelors: 0.2%
  • Doctoral Degree (PHd) : 0.1%

Most Common Bachelors Degree Majors

  • For Business undergraduate majors this income ranks between the 34.7th and 74.1th percentiles.
  • For Education Administration and Teaching undergraduate majors this income ranks between the 49th and 78.4th percentiles.
  • For Social Sciences undergraduate majors this income ranks between the 33th and 72.5th percentiles.
  • For Engineering undergraduate majors this income ranks between the 25.8th and 62.1th percentiles.
  • For Criminal Justice and Fire Protection undergraduate majors this income ranks between the 73.4th and 80.3th percentiles.
  • For Fine Arts undergraduate majors this income ranks between the 38.9th and 60.2th percentiles.
  • For Psychology undergraduate majors this income ranks between the 34th and 63.5th percentiles.
  • For Computer and Information Sciences undergraduate majors this income ranks between the 58.5th and 82.7th percentiles.
  • For History undergraduate majors this income ranks between the 39.7th and 62.9th percentiles.
  • For Medical and Health Sciences and Services undergraduate majors this income ranks between the 17.9th and 88th percentiles.
Note: The source data only records undergraduate degree majors, even if a person continues to study.

Treemap of Undergraduate Majors

Methodology and Assumptions

This data was sourced from the person-level data recorded by the American Communities Survey. The version of the survey used was the most recent 5 year revision for data recorded from 2013-2017. These results represent 65,351 Postal Service Mail Sorters, Processors, and Processing Machine Operators. The occupation code that was used to generate these results e was 5560 to read more about the occupation codes that the ACS and Census use. These results were generated in R using raw data from the ACS and precalculated in a batch. This data includes all individual income for the survey respondent, so some of the people may have a wage job as well as other income sources. I did not limit to wage income, because many occupations have high portions of entrepreneurs (CEOs, doctors, tradespeople).

Exclusions and Filters Applied:
  • Filtered for people who reported working at least 30 hours a week.
  • High School Graduates and GED graduates were original 2 separate categories that I combined.
  • Anything below High School Graduates is combined into a separate category. I did not include these on the page for space reason but I can.
  • The data has data for associate degree holders and some college and these values are mostly in between the high school and bachelors samples. There doesn't seem to be a significant difference between some college and an associates degree.
  • All ages are included and not separated. I did some initial testing and there is a difference if the data is split out by age, but I wasn't able to consolidate the data into a way that would make it fast to interact with and avoid being too complicated.
  • There may be some confusion around a masters degree vs a professional degree beyond a masters. This was a distinction made in the original raw data that I decided to keep. Because the data is collected by polling people individually, some of the respondents may have mixed up the difference depending on how they phrased their response.
    • Masters Degree : MBA, Masters in Something
    • Professional Degree beyond a Bachelors Degree: Law Degree, Medical School, generally these degrees are credentials for specific careers.
    • Doctoral Degree: PHd