Apply now Job no: 584243 Work type: Full-time Location: Flexible, Geelong - Waurn Ponds, Melbourne - Burwood Categories: Finance
The Senior Analyst, Student Load Optimisation is responsible for leveraging data and analytics to optimise the university's student load, maximise resource utilisation and support the university's strategic enrolment goals. This position uses a range of tools, data sources and data acquisition methodologies to deliver data, reports and visualisations that underpin and inform student load modelling and planning.
Key Responsibilities
* Analyse student enrolment data to identify trends, patterns, and factors that impact student load and develop predictive models to forecast student demand and load for various courses and programs.
* Contribute to the development of strategies to optimise student load across faculties, courses, and trimesters to maximise resource utilisation and revenue and identify opportunities to balance student numbers and ensure course offerings align with demand.
* Work with faculties and schools to manage capacity, reduce under‐enrolled courses, and promote high‐demand programs and advise on potential risks and opportunities related to student load and enrolment patterns.
* Provide data‐driven insights and recommendations to support the university's strategic planning for student load growth and develop long‐term forecasting models to predict enrolment trends and plan for future capacity requirements.
* Actively engage with a diverse range of stakeholders, analyse problems and weigh up a range of options to negotiate inclusive and accessible solutions. Implement solutions, evaluate effectiveness and adjust actions as required.
Required Qualifications
* Postgraduate qualifications or progress towards postgraduate qualifications and extensive relevant experience; or
* Extensive experience or an equivalent combination of relevant experience and/or education/training in business information systems, modern data management platforms.
* Proficiency in data modelling and statistical and analytical software (e.g., R, Python, SAS).
* Proven experience developing and maintaining IBM Planning Analytics (TM1) models, including cube design, rules, and TurboIntegrator (TI) processes.
* Proficiency in use of data analysis, reporting and visualisation tools.
* Knowledge of student enrolment and/or load planning in a higher education environment preferred.
Benefits
At Deakin you will have access to benefits such as a variety of leave options including generous parental leave and the ability to purchase additional leave; flexible working arrangements to help manage your work‐life balance; ongoing learning and development opportunities to grow your career; an inclusive and supportive culture and environment to work in, both online and on campus.
Pre‐employment safety and suitability checks
In accordance with the National Higher Education Code to Prevent and Respond to Gender‐based Violence, appointment to this role is subject to successful completion of relevant pre‐employment checks, including Working With Children Checks and candidate gender‐based violence declarations. Candidates may be asked to declare whether they have been investigated for an allegation of Gender‐based Violence, or determined to have engaged in conduct that constitutes Gender‐based Violence during the course of their previous employment, or otherwise in a legal process. A declaration is not required from individuals who have experienced gender‐based violence. A 'Yes' response does not automatically exclude a candidate from employment, and any information provided will be treated confidentially and considered only for relevance to the role and the University's safety obligations.
We value diversity and aim to build an inclusive environment that champions, embraces and respects differences. We support and encourage applications from Aboriginal and Torres Strait Islander people, and people of all abilities, cultures, sexual orientation, and genders.
Advertised: 23 Apr 2026 AUS Eastern Standard Time
Applications close: 10 May 2026 AUS Eastern Standard Time
#J-18808-Ljbffr