Overview
Summary
Comparison table
Indicator
Laboratory Manager
Total employment
Employed persons
3,000
12,049,400
Median age
45 years
40 years
Full-time share
85.3%
64.2%
Part-time share
14.5%
35.8%
Female employment share
48.3%
48.5%
Male employment share
51.6%
51.5%
Gender segregation intensity scale
Gender balanced
Gender balanced
Indigenous employment share
0.6%
2.2%
Main employing industry
Professional, Scientific and Technical Services
Health Care and Social Assistance
Note: N/A values indicate data are not available due to confidentiality or data reliability requirements.
Occupation overview
Laboratory Managers plan, organise, direct, control and coordinate the operations of a research, medical or production laboratory to ensure quality standards are met and health and safety standards comply with regulatory frameworks.
What the occupation involves
Implements, manages and oversees protocols, and ensures health and safety standards in the laboratory comply with regulatory frameworks Maintains laboratory equipment and inventory levels Trains technicians on the proper use of equipment and safety procedures to follow in the laboratory Manages the daily operations of a laboratory, including the supervision of employees and schedule of activities Monitors and ensures all laboratory operations are performed according to specifications Reviews the studies, tests and analysis performed in the laboratory Plans, organises and coordinates the quality management processes within the laboratory
Common occupation titles
No alternative occupation titles are listed for this occupation.
Specialisations
No specialisations are listed for this occupation.
Skill level (education and experience level)
Skill level 1 equivalent to a university level qualification (Bachelor degree or higher).
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
Managers (1)
Education, Health, Welfare and Other Specialist Managers (14)
Miscellaneous Specialist Managers (149)
Employment
Industries
Top 10 most common industries, 2021
Chart
Comparison table
Laboratory Manager Total employment
Industry
Share of occupation
Industry
Share of occupation
Professional, Scientific and Technical Services
26.6%
Health Care and Social Assistance
14.5%
Education and Training
23.7%
Retail Trade
9.1%
Health Care and Social Assistance
17.6%
Construction
8.9%
Manufacturing
13.1%
Education and Training
8.8%
Public Administration and Safety
3.7%
Professional, Scientific and Technical Services
7.8%
Construction
2.6%
Public Administration and Safety
6.6%
Mining
2.3%
Accommodation and Food Services
6.5%
Agriculture, Forestry and Fishing
1.7%
Manufacturing
5.9%
Wholesale Trade
1.6%
Transport, Postal and Warehousing
4.5%
Electricity, Gas, Water and Waste Services
0.9%
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
Laboratory Manager Total employment
State / Territory
Employment
Share of occupation
Employment
Share of occupation
New South Wales
820
27.6%
3,684,200
30.6%
Victoria
790
26.5%
3,162,900
26.2%
Queensland
560
18.9%
2,444,100
20.3%
South Australia
280
9.2%
839,400
7.0%
Western Australia
370
12.4%
1,306,200
10.8%
Tasmania
70
2.2%
254,700
2.1%
Northern Territory
30
0.9%
107,000
0.9%
Australian Capital Territory
70
2.2%
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
Age group
Laboratory Manager
Total employment
15–24 years
0.9%
14.3%
25–34 years
15.0%
22.7%
35–44 years
30.7%
22.3%
45–54 years
29.0%
20.4%
55–64 years
20.7%
15.3%
65–74 years
3.4%
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
Laboratory Manager
Total employment
Female
48.3%
48.5%
Male
51.6%
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%.
