Project Info

GrowthAndJobs thumbnail

Team Name


Team Members

Aqeel and 3 other members with unpublished profiles.

Project Description


How can we use open datasets to help job-seekers and entrepreneurs take advantage of their skills and emerging market opportunities?


Our solution uses machine learning and AI to predict changes in the job market, at a national and regional level.

JobsAndGrowth allows job-seekers to make the most of their abilities. You can find out what jobs will be in demand in what state and hwo much they will pay, using AI predictions for up to 5 years into the future. The provides job-seekers with a broad array of choices that they can make, to balance different incentives. Navigating these choices is easy with our simple, intuitive, and reactive interface, which allows you to search and filter by the criteria that are relevant to you. Interested making a career change to a similar job in your state? We can help. Interested in moving interstate to take advantage of higher average wages for your career? We've got you covered.

For entrepreneurs, our platform provides a rich interface to visualize, at a glance, the current market trends in your industry and breakdowns of your income and expenses. You can see how historical trends in profits and expenses and average profit rates for businesses in your field. We also connect you to the job market.

Data Story



  • Taxation Statistics 2016-17, Snapshot Table 7: We used this dataset to get see how number of employees and salary vary for each 4-digit ANZSCO level and each State/Territory
  • Taxation Statistics 2016-17 Individuals, Table 14: We used this dataset to see how tax statistics (income, dedeuctables, expenses etc.) vary in each occupation over time. Table 14b has aggregated statistics dating back to 2010-2011. We used this dataset to build models which predict future wage growth.

Labour Market Information Portal (LMIP)


Evidence of Work



Project Image

Team DataSets

This team does not currently have any datasets.

Challenge Entries

Training AI models to deliver better human outcomes

For an outcome create two AI models based on contrasting incentive systems and examine the differing impacts on the defined outcome.

Go to Challenge | 12 teams have entered this challenge.

Australia’s Future Employment

Choose one of the following questions to address: 1. How can recent and future changes in the labour market help prepare young people for job opportunities? 2. What can we learn from case studies of regional labour markets? For example, what does rapid change in the industries or occupations within a region tell us about the needs of employers/workers in other regional labour markets

Go to Challenge | 38 teams have entered this challenge.

ATO for individuals

How can ATO and other Australian public data be used to help the community fill employment opportunities?

Go to Challenge | 27 teams have entered this challenge.

Leveraging innovation precincts to drive economic prosperity.

How might we build on interaction between businesses and research institutions in Australian innovation precincts, to boost business capability, growth, and job creation?

Go to Challenge | 23 teams have entered this challenge.

🌟 Canberra 2029 – Inclusive; Progressive; Connected

How do we use data from the past to predict a better future for Canberra? How do we best support the diversity of our community? Optimise the way we travel and transport goods throughout our city? Predict the jobs of the future – and the skills needed for them? Connect our citizens with their environment?

Go to Challenge | 21 teams have entered this challenge.