Janus | One-stop Career Service

Project Info

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Team Members


Shivam Patel , John Nguyen , Phoenix Nguyen and 1 other member with an unpublished profile.

Project Description


PROBLEM STATEMENT AND SOLUTION

To address the demand for employment, we build an end-to-end, user-friendly, robust and dynamic platform called 'Janus' to reimagine digital employment services in Australia. Janus will be available both as a website and as a mobile application. Along with the digital platform, we provide API functionality for third-party applications.

Prototype

Webapp
Mobile app

USER:
We cater to users of all kinds: young adults, fresh graduates, people with disabilities, workers aged more than 55, to someone who wishes to get back to work or make a career change.

KEY FEATURES:

  • Chatbot: an alternative way for the user to navigate through features that match their needs. This will enhance the overall user experience and help save user’s time and efforts to explore dozens of links. Our chatbot is augmented with a speech recognition functionality that would enhance accessibility for people with disabilities.

  • Recommendation employment opportunities based on his skill set, which he has acquired from his current and previous jobs. We have used the Australian Skills Classification dataset to create a network graph connecting similar jobs and skills and related to future job aspects. We have also used state-of-the-art NLP and Machine Learning techniques to create word vectors and find similarities in job descriptions with different titles. Moreover, an extensive search engine is built using Elasticsearch and a fuzzy matching algorithm to help us address the issue of multiple terms used to refer to the same job titles or skills.

  • Show the skill ranking by their popularity as required for that job, along with the locations where the job is in the most demand. Further, based on the requirements, we also provide the users with education opportunities, including online courses, certifications programs and university degrees.

  • Moving further, Janus also offers several features dedicated to the youth. Many young people do not have a single career path in their minds. The application would allow such users to list out a set of jobs they are interested in. Then, it will find out job clusters sharing similar skills and characteristics and help the user identify the transferable skills required by most of the jobs. This would, in turn, help the younger users improve their adaptability and have flexibility in their career paths. Along with upskilling guidance, we also provide the users with interview preparation.

  • Additionally, we have a special feature that caters to users who do not have much idea about their preferred careers. The application would provide them with a quick and straightforward test to help explore and understand the user’s personality and interests and, thus, in turn, recommend the relevant career options.

  • From a broader perspective, the job market changes all the time, and new job titles are created which require newer skills. We address this requirement by developing a dynamic database. To create the dynamic database, we connect to the ABS interface and make our system periodically retrieve the employment by ANZSCO occupations data so that our recommendations are kept up to date. The dynamic database of Janus is also enhanced by a gamification design which encourages users to provide feedback and contribute to the database simply by answering questions about whether they think the recommendations are helpful and by getting to know the other skills required by a particular job. Moreover, the validation process of the user-contributed content is partially automated with a credibility scoring model.

All in all, we present an extensive AI-driven application, with job recommendations, skill enhancement, API functionality, interview preparation and much more to cater to the emerging needs of the Digital Employment Services for all types of people including elders and people with disabilities in Australia.


#jobs #jobsseekers #employment #employer #development #career #skills #certification #future #ml #ai #vulnerableaustralians #nationalskillscommission #absdataapi #digitalgovernmentsevices #youth #education #publicdata #government

Data Story


THE DATA STORY BEHIND JANUS

We have incorporated a lot of datasets in building Janus. All the datasets have given us beneficial insights at each stage of our development.

Key Motivations:
Using the seasonally adjusted data of the past 30 years (May 1989 to May 2019) from ABS Labour Force, we found out that a substantial share of people looks out for career enhancement after getting their first job. Moreover, from the 'Employers' Insights on the Australian Labour Market - 2020 Dataset', we found out that the COVID pandemic had a great impact on employment in Australia, and it needs to be tackled well. Further from the 'Occupation Projections - Five Years to November 2025 Dataset', we understood that there would be over 1 million new job opportunities in various fields by November 2025. Considering all these, we built a robust and unique solution that aims at enhancing the digital employment services in Australia.

Datasets:
Below, we present how we have incorporated the various open datasets for building Janus.

  • Employers' Insights on the Australian Labour Market - 2020 Dataset: This dataset helped us understand the various useful insights of employers on the Australian job market, which helped us understand the various issues and difficulties faced by Australians currently in the job market and thus eventually mould our solution accordingly.

  • Jobs Services Australia Vacancy Dataset: Along with helping in recommending the users with career options, this dataset primarily helps the job seekers find the location where the desired job would be in the most demand. Moreover, this data source helped us understand the skills shortages for numerous states for the various associated occupations.

  • Australian Skills Classification Dataset: We used this dataset to discover various relations among occupations and how they are related to different skills. This, in turn, helps the user to explore future employment opportunities.

  • IVI Detailed Occupation Data - March 2006 Onwards Dataset: This dataset helped us understand the overall shift in the career options among Australians, which guided us to ideate our solution.

  • ABS Data API - Employment by ANZSCO Occupations Dataset: After connecting to the ABS interface, our system periodically retrieves the employment by ANZSCO occupations data so that our recommendations are kept up to date.

  • Occupation Projections - Five Years to November 2025 Dataset: Using this data, we make the user learn about the future employment projections in various occupations and the skills required for the occupations.

  • My Next Move Dataset: For users having not had many ideas about their preferred career choices, this dataset helped us organize quick and straightforward tests to help explore and understand the user’s personality and interests and, thus, recommend the relevant career options to them.

  • Higher Education Statistics Student Dataset: This dataset gave us insights into the various university degrees that the users can consider to develop skills required for their future job.

  • Udemy Affiliate API Dataset: This dataset gave us insights into the various online courses and certification programs that the users can consider to develop skills required for their future job.

  • ABS Labour Force Australia Dataset - July 2021: This dataset helped us gain insight into the current statistics for employment, unemployment and underemployment in Australia.


Evidence of Work

Video

Homepage

Project Image

Team DataSets

ABS Data API - Employment by ANZSCO Occupations Dataset

Description of Use After connecting to the ABS interface, our system periodically retrieves the employment by ANZSCO occupations data so that our recommendations are kept up to date.

Data Set

Employers' Insights on the Australian Labour Market - 2020 Dataset

Description of Use This dataset helped us understand the various useful insights of employers on the Australian job market, which helped us understand the various issues and difficulties faced by Australians currently in the job market and thus eventually mould our solution accordingly.

Data Set

ABS Labour Force Australia Dataset - July 2021

Description of Use This dataset helped us gain insight into the current statistics for employment, unemployment and underemployment in Australia.

Data Set

Jobs Services Australia Vacancy Data

Description of Use Along with helping in recommending the users with career options, this dataset primarily helps the job seekers find the location where the desired job would be in the most demand. Moreover, this data source helped us understand the skills shortages for numerous states for the various associated occupations.

Data Set

Higher Education Statistics Student Dataset

Description of Use This dataset gave us insights into the various university degrees that the users can consider to develop skills required for their future job.

Data Set

Udemy Affiliate API Dataset

Description of Use This dataset gave us insights into the various online courses and certification programs that the users can consider to develop skills required for their future job.

Data Set

My Next Move Dataset

Description of Use For users having not much idea about their preferred career choices, this dataset helped us organize quick and straightforward tests to help explore and understand the user’s personality and interests and, thus, recommend the relevant career options to them.

Data Set

IVI Detailed Occupation Data - March 2006 Onwards Dataset

Description of Use This dataset helped us understand the overall shift in the career options among Australians, which guided us to ideate our solution.

Data Set

Occupation Projections - Five Years to November 2025 Dataset

Description of Use Using this data, we make the user learn about the future employment projections in various occupations along with the skills required for the occupations.

Data Set

Australian Skills Classification Dataset

Description of Use We used this dataset to discover various relations among occupations and how they are related to different skills. This, in turn, helps the user to explore future employment opportunities.

Data Set

Challenge Entries

Meeting the needs of vulnerable Australians during a global pandemic

How can data help us better understand and meet the needs of vulnerable Australians such as older Australians and Australians with a disability as we navigate through the complexities of a global pandemic?

Eligibility: Must use at least one open dataset.

Go to Challenge | 6 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.

Reimagining Digital Government Services

How can we re-imagine digital government services in Australia to enable a seamless experience for people of all abilities.

Eligibility: Must use at least one open dataset.

Go to Challenge | 26 teams have entered this challenge.

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.

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.