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Seekareer


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Seekareer

Project Info

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Team Name


Seekareer


Team Members


Kaedyn Cui , Stephanie Chow , Ching-lee Sun , Kin Wah LAU

Project Description


Australia unemployment rate is rising sharply because of COVID-19. More and more people are hired as casual staff, and some are looking for a permanent job. To facilitate both businesses and job seekers to find their ideal match, Seekareer is here to help! Compared to current job-seeking applications, Seekareer is more direct that employees can apply for multiples jobs with the same title or in the same industry. You do not need to check it one by one nor missed out on any potential job. For the Human Resources department, it reduced the cost of AI selection and integrate the hiring process. HR can see the filtered keywords as hashtag features, and it shows how candidates see themselves. By using and analyzing the datasets that the Australian government has provided, Seekareer combines the present covid situation with clear skills classification to promote the chances of getting the right people into the right workplace.


#career #jobseeking #seekareer #jobhunting #hiredemployee #skillset

Data Story


We utilized employment-related data with COVID-19 real-time info to help our project users to find their ideal match in more efficient and effective ways.


Evidence of Work

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Team DataSets

Australian Bureau of Statistics (ABS) Data API (Beta)

Description of Use To analyse the employment and income situation based on career types.

Data Set

ABS Labour Statistics

Description of Use To monitor, predict and review nationwide employment and unemployment statistics, as well as understanding the average earnings and work hours.

Data Set

APS Digital Career Pathways

Description of Use To identify career types and corresponding positions.

Data Set

ABS Industry Statistics

Description of Use To identify the use of information technology and related practices by Australian businesses.

Data Set

Australian National University CRISPER data within Confluent Cloud

Description of Use To monitor COVID in a real-time situation and to predict when/where the businesses require certain type of employees.

Data Set

Challenge Entries

Youth education and employment

How might we use publicly available data to identify education and employment opportunities for our youth?

Go to Challenge | 25 teams have entered this challenge.

Most outstanding benefit to the residents of Tasmania

How can we use Open Data to most benefit residents of Tasmania?

Eligibility: Must use Tasmanian data.

Go to Challenge | 6 teams have entered this challenge.

Exploring the National Skills Commission’s Australian Skills Classification

How can the general public learn about and be encouraged to interact with the Australian Skills Classification to identify skills within occupations, identify their own skillsets and identify transferability to other occupations of interest?

Eligibility: Participants must use the Australian Skills Classification dataset.

Go to Challenge | 25 teams have entered this challenge.

Living in a post-pandemic world

How can we use real-time data to assist with the preparation and ongoing management of living with Covid-19 as we progress towards a post-pandemic Australia and New Zealand?

Eligibility: Contestants should use Confluent as part of their solution and the CRISPER dataset as part of their solution.

Go to Challenge | 13 teams have entered this challenge.

Create a solution to a customer need using the ABS Data API

We are excited to provide innovators with machine to machine access to ABS Data and see what exciting customer solutions can be created. Here is a chance to draw in ABS Data and answer an important question through visualisation, mapping or even blending with other data sources. Create a solution to a customer need using data drawn from the ABS Data API.

Eligibility: Teams are encouraged to use datasets from a variety of sources, but at least one must be drawn from the ABS Data API.

Go to Challenge | 20 teams have entered this challenge.