The Quantitative Analysis discipline seeks university graduates with numeric and analytical skills to join our team of professional analysts at the Department of Employment. Quantitative Analysis graduates have the opportunity to apply specialist skills gained through university to real-world issues and diverse data sources. Our programme of formal and on-the-job training supported by experienced supervisors will see you develop skills in data analysis using industry-standard software like SAS and SQL.
What our graduates do
As a graduate in the Quantitative Analysis discipline you will be involved in monitoring, measuring and evaluating the outcomes of the Department’s labour market programmes. Your specialist skills will be challenged as you deliver evidence-based advice to inform the Department’s current and future policy agenda. Examples of what our graduates do include:
- Analysing and reporting on the labour market outcomes of disadvantaged groups, including youth, migrants and Indigenous Australians.
- Using sophisticated data matching, predictive modelling and analytics to develop differentiated risk profiles and provide insight into market behaviour in the employment services industry.
- Measuring the effectiveness of assistance provided to unemployed Australians through survey and administrative data.
- Evaluate the effectiveness of employment related interventions through the use of randomised control trials.
- Developing and reporting on appropriate measures of performance for publically-funded employment services.
- Investigating the factors that contribute to long-term unemployment.
What we are looking for
We are seeking highly motivated graduates with degrees in one of the following disciplines or any other field with a focus on quantitative analysis and problem solving. We are interested in people with enthusiasm, good work ethic and an attitude open to learning and innovation. Strong interpersonal and communication skills are also highly valued.
- Applied Statistics
- Actuarial Studies
- Social Research
- Computer Science
- Information Technology