Overview
Summary
Comparison table
Indicator
Chemical Production Machine Operator
Total employment
Employed persons
3,400
12,049,400
Median age
43 years
40 years
Full-time share
80.2%
64.2%
Part-time share
19.8%
35.8%
Female employment share
31.4%
48.5%
Male employment share
68.5%
51.5%
Gender segregation intensity scale
Moderately male dominated
Gender balanced
Indigenous employment share
1.4%
2.2%
Main employing industry
Manufacturing
Health Care and Social Assistance
Note: N/A values indicate data are not available due to confidentiality or data reliability requirements.
Occupation overview
Chemical Production Machine Operators operate machines to produce chemical goods such as soaps, detergents, pharmaceuticals, toiletries and explosives.
What the occupation involves
Sets up and prepares machines to produce chemical goods Measures the ingredients used in chemical products to be mixed and blended Operates crushing machines or mills to grind and pulverise solid chemicals and other materials to a specified size suitable for processing Monitors the removal of the ground product from machines, and inspects and tests samples of products for quality and consistency Performs regular checks and basic maintenance on processing machines, and reports any faults Follows safety procedures and guidelines to ensure a safe working environment Records production data and maintains production logs
Common occupation titles
No alternative occupation titles are listed for this occupation.
Specialisations
Note: Specialisations are examples of roles in within this occupation and are not separate OSCA occupations.
Skill level (education and experience level)
Skill level 4 equivalent to a lower‑level Vocational Education and Training (VET) qualification (Certificate II or III).
Note: While skill levels are described using formal education levels, some people use a combination of informal learning, on-the-job training and personal experience to achieve an equivalent level.
Licensing or registration requirements
No licensing or registration requirements are listed for this occupation.
OSCA structure
Machinery Operators and Drivers (7)
Machine and Stationary Plant Operators (73)
Employment
Industries
Top 10 most common industries, 2021
Chart
Comparison table
Chemical Production Machine Operator Total employment
Industry
Share of occupation
Industry
Share of occupation
Manufacturing
69.1%
Health Care and Social Assistance
14.5%
Wholesale Trade
6.7%
Retail Trade
9.1%
Retail Trade
5.0%
Construction
8.9%
Mining
2.9%
Education and Training
8.8%
Administrative and Support Services
1.4%
Professional, Scientific and Technical Services
7.8%
Construction
1.3%
Public Administration and Safety
6.6%
Health Care and Social Assistance
1.3%
Accommodation and Food Services
6.5%
Agriculture, Forestry and Fishing
1.0%
Manufacturing
5.9%
Other Services
0.6%
Transport, Postal and Warehousing
4.5%
Professional, Scientific and Technical Services
0.6%
Financial and Insurance Services
3.7%
Note: N/A values indicate data are not available due to confidentiality or data reliability requirements.
States and territories
Employment distribution by states and territories, 2021
Summary
Comparison table
Chemical Production Machine Operator Total employment
State / Territory
Employment
Share of occupation
Employment
Share of occupation
New South Wales
1,100
32.4%
3,684,200
30.6%
Victoria
1,200
34.8%
3,162,900
26.2%
Queensland
520
15.4%
2,444,100
20.3%
South Australia
140
4.2%
839,400
7.0%
Western Australia
390
11.6%
1,306,200
10.8%
Tasmania
40
1.2%
254,700
2.1%
Northern Territory
10
0.3%
107,000
0.9%
Australian Capital Territory
10
0.1%
248,600
2.1%
Note: N/A values indicate data are not available due to confidentiality or data reliability requirements.
Age and sex
Employment distibution by age group and sex, 2021
Charts
Comparison table
Chemical Production Machine Operator
Age group
Chemical Production Machine Operator
Total employment
15–24 years
7.1%
14.3%
25–34 years
22.6%
22.7%
35–44 years
24.8%
22.3%
45–54 years
24.6%
20.4%
55–64 years
17.7%
15.3%
65–74 years
3.2%
4.3%
75 years and over
0.2%
0.6%
Note: N/A values indicate data are not available due to confidentiality or data reliability requirements.
Sex
Chemical Production Machine Operator
Total employment
Female
31.4%
48.5%
Male
68.5%
51.5%
Note: N/A values indicate data are not available due to confidentiality or data reliability requirements.
OSCA occupation profiles data
This file contains data available from the OSCA Occupation Profile page.
Use of this data must include the relevant attribution text provided.
OSCA Occupation data - 2021 Census.xlsx
xlsx
1236447
Download
Occupation Standard Classification for Australia (OSCA)
Occupation Standard Classification for Australia (OSCA) is the skill-based classification used to categorise occupations across the Australian labour market. OSCA is used to define occupations across all official occupational statistics. OSCA replaces the Australian and New Zealand Standard Classification of Occupations (ANZSCO).
Each job is classified to one, and only one, group of jobs at each level of the classification with no overlaps. This prevents the accidental double-counting of roles within the Australian labour market. For more information about OSCA, visit the What is OSCA information page, or the ABS website.
Source
ABS, 2021 Census of Population and Housing based on usual place of residence (Custom Report). OSCA Experimental Estimates.
Caveats
The 2021 Census was taken at a time when many parts of Australia were under COVID-19 restrictions. Occupations were unevenly impacted by restrictions on face-to-face interactions and travel.
Results may differ from standard ABS Census occupation outputs due to experimental coding to OSCA.
Occupation and industry data refer to a person’s main job in the week prior to the Census, reflecting their employment at that point in time.
The ABS perturbs data to protect individual privacy. For more information, see: https://www.abs.gov.au/statistics/microdata-tablebuilder/tablebuilder/confidentiality-and-relative-standard-error
Suppression rules are applied based on occupation employment size, using pre-rounded employment values:
Fewer than 50 employed persons are suppressed to protect confidentiality and prevent identification of individuals.
50–499 employed persons display total employment only; all other data are suppressed.
500–2,000 employed persons have datasets suppressed where they contain more than two variables.
More than 2,000 employed persons display full profiles with no suppression.
Employment values are rounded after suppression rules are applied. Values below 1,000 are rounded to the nearest 10, and values of 1,000 or more are rounded to the nearest 100.
Approximately 8% of employed persons in the 2021 Census were classified as ‘Employed, away from work’. Unless otherwise stated, these people are included in all employment data presented.
Approximately 8% of employed persons in the 2021 Census were classified as ‘Employed, away from work’. Unless otherwise stated, these people are included in all employment data presented.
The sum of 6-digit employment may not equal the parent 4-digit total due to data perturbation and the exclusion of not further defined (nfd) occupations.
The sum of percentages may not equal 100% due to several factors, including: perturbation, rounding and the exclusion of specific responses from the denominator.
Non-zero proportions under 0.1% are reported as <0.1%.
Definitions
Employment in main job
This is the number of people employed in an occupation as their main job.
Employment status
Full-time share: This is the proportion of people employed in an occupation who work full-time (those who worked 35 hours or more during the week of the census) in their main job.
Part-time share: This is the proportion of people employed in an occupation who work part-time (those who worked less than 35 hours during the week of the census) in their main job.
Note: For the proportions of full-time and part-time workers, those who were classified as ‘Employed, away from work’ in the week prior to the Census (accounting for approx. 8% of total national employment), have been excluded from the denominator. These people were employed but did not work any hours due to temporary reasons such as leave or work disruption.
Some occupations show a higher rate of people classified as ‘Employed, away from work’. This reflects a combination of COVID-19 restrictions and structural work patterns in some occupations (for example, where shift work, or fly-in, fly-out (FIFO) arrangements mean more workers are likely to be away from work at any given time).
The downloadable data file includes a column highlighting occupations that recorded more than 10% of employment as away from work during the week of the Census.
Median age
This is the age right in the middle of all workers in an occupation, half are younger and half are older.
Employment by gender
This is the proportion of people in an occupation who are male and female.
Gender Segregation Intensity: This is determined using the proportion of males and females within an occupation.
Gender balanced - Less than 60% of both genders
Moderately female or male dominated - Between 60-75% of dominant gender
Highly female or male dominated - Between 75-90% of dominant gender
Almost completely female or male dominated - 90% and above of dominant gender
You can find more information about the Gender Segregation Intensity Scale in the JSA Gender Economic Equality Study .
Indigenous employment share
This is the proportion of people who identified as Aboriginal and/or Torres Strait Islander.
Main employing industry
This is the industry that the greatest proportion of people within this occupation are employed in.
Industries are presented at the ANZSIC Division (1-digit) level.
OSCA descriptions
ABS, 2024, OSCA - Occupation Standard Classification for Australia
https://www.abs.gov.au/statistics/classifications/osca-occupation-standard-classification-australia/2024-version-1-0
Source
ABS, 2021 Census of Population and Housing based on usual place of residence (Custom Report). OSCA Experimental Estimates.
Caveats
The 2021 Census was taken at a time when many parts of Australia were under COVID-19 restrictions. Occupations were unevenly impacted by restrictions on face-to-face interactions and travel.
Results may differ from standard ABS Census occupation outputs due to experimental coding to OSCA.
Occupation and industry data refer to a person’s main job in the week prior to the Census, reflecting their employment at that point in time.
The ABS perturbs data to protect individual privacy. For more information, see: https://www.abs.gov.au/statistics/microdata-tablebuilder/tablebuilder/confidentiality-and-relative-standard-error
Suppression rules are applied based on occupation employment size, using pre-rounded employment values:
Fewer than 50 employed persons are suppressed to protect confidentiality and prevent identification of individuals.
50–499 employed persons display total employment only; all other data are suppressed.
500–2,000 employed persons have datasets suppressed where they contain more than two variables.
More than 2,000 employed persons display full profiles with no suppression.
Employment values are rounded after suppression rules are applied. Values below 1,000 are rounded to the nearest 10, and values of 1,000 or more are rounded to the nearest 100.
Industries are presented at the ANZSIC Division (1-digit) level. Industries with very small employment shares may not be visible.
The sum of industry percentages may not equal 100% due to data perturbation, suppression of small values, rounding, and the exclusion of very small industries, and not stated and inadequately described responses.
Non-zero proportions under 0.1% are reported as <0.1%.
Source
ABS, 2021 Census of Population and Housing based on usual place of residence (Custom Report). OSCA Experimental Estimates.
Caveats
The 2021 Census was taken at a time when many parts of Australia were under COVID-19 restrictions. Occupations were unevenly impacted by restrictions on face-to-face interactions and travel.
Results may differ from standard ABS Census occupation outputs due to experimental coding to OSCA.
Occupation data refer to a person’s main job in the week prior to the Census, reflecting their employment at that point in time.
The ABS perturbs data to protect individual privacy. For more information, see: https://www.abs.gov.au/statistics/microdata-tablebuilder/tablebuilder/confidentiality-and-relative-standard-error
Suppression rules are applied based on occupation employment size, using pre-rounded employment values:
Fewer than 50 employed persons are suppressed to protect confidentiality and prevent identification of individuals.
50–499 employed persons display total employment only; all other data are suppressed.
500–2,000 employed persons have datasets suppressed where they contain more than two variables.
More than 2,000 employed persons display full profiles with no suppression.
Employment values are rounded after suppression rules are applied. Values below 1,000 are rounded to the nearest 10, and values of 1,000 or more are rounded to the nearest 100.
The sum of state and territory percentages may not equal 100% due to data perturbation, rounding, and the exclusion of ‘Other Territories’ responses from the denominator.
Percentages are based on unrounded data and may not align with calculations using the rounded employment counts shown.
Non-zero proportions under 0.1% are reported as <0.1%.
Source
ABS, 2021 Census of Population and Housing based on usual place of residence (Custom Report). OSCA Experimental Estimates.
Caveats
The 2021 Census was taken at a time when many parts of Australia were under COVID-19 restrictions. Occupations were unevenly impacted by restrictions on face-to-face interactions and travel.
Results may differ from standard ABS Census occupation outputs due to experimental coding to OSCA.
Occupation and industry data refer to a person’s main job in the week prior to the Census, reflecting their employment at that point in time.
The ABS perturbs data to protect individual privacy. For more information, see: https://www.abs.gov.au/statistics/microdata-tablebuilder/tablebuilder/confidentiality-and-relative-standard-error
Suppression rules are applied based on occupation employment size, using pre-rounded employment values:
Fewer than 50 employed persons are suppressed to protect confidentiality and prevent identification of individuals.
50–499 employed persons display total employment only; all other data are suppressed.
500–2,000 employed persons have datasets suppressed where they contain more than two variables.
More than 2,000 employed persons display full profiles with no suppression.
Employment values are rounded after suppression rules are applied. Values below 1,000 are rounded to the nearest 10, and values of 1,000 or more are rounded to the nearest 100.
The sum of age group percentages may not equal 100% due to data perturbation and rounding.
Gender Segregation Intensity: This is determined using the proportion of males and females within an occupation.
Gender balanced — Less than 60% of both genders
Moderately female or male dominated — Between 60–75% of dominant gender
Highly female or male dominated — Between 75–90% of dominant gender
Almost completely female or male dominated — 90% and above of dominant gender
You can find more information about the Gender Segregation Intensity Scale in the JSA Gender Economic Equality Study .
Non-zero proportions under 0.1% are reported as <0.1%.
