Applications received by invitation. Please continue if you received an email from the recruiter to apply for this position. a. About the Opportunity This role will include teaching-related duties, such as presenting classes (depending on qualifications and unit of study, this could include lectures, tutorials, practical classes or workshops), and marking Casual rates for academic teaching duties include both the presentation or delivery time as well as associated working time (including preparation, reasonably contemporaneous marking and student consultation) Pay rates for other academic casual duties can be found within the University of Sydney Enterprise Agreement and will be applied where relevant In order to meet TEQSA requirements, applicants must possess a qualification one level higher than the level they are applying for, or possess equivalent professional experience This role provides an opportunity to contribute to world class education and innovation The Discipline of Business Analytics is a group that combines academics from statistics/econometrics, management science and computer science. We are engaged in all aspects of analysing data, making forecasts and building models to assist in management decisions. The Discipline has research strengths in the areas of financial time series and quantitative risk management; business and economic forecasting; econometrics and Bayesian statistics; computationally intensive estimation; supply chain management and scheduling theory. The group is building up expertise in machine learning and is open to appointing teachers and researchers in other emerging fields in business analytics such as text analytics. b. About you The University values courage and creativity; openness and engagement; inclusion and diversity; and respect and integrity. We see the importance of recruiting talent aligned to these values, and are looking for casual academic staff who can also: present relevant qualifications or experience provide evidence of high-quality teaching experience in one or more of the major areas in Business Analytics, namely: statistics and data analysis statistical learning risk analytics time series analysis machine learning operations management operations research management science successfully engage students and ensure a supportive and positive learning experience demonstrate successful teamwork and a collegial approach use initiative and contribute effectively to the unit of study they are teaching on function in a flexible and ever-changing environment abide by the University's principles of diversity and inclusion ensure a safe working environment for self and others. Applications Close No End Date