Data Modelers

Vor 2 Tagen


Sydney, Österreich Randstad Education Australia Vollzeit

Senior Data Modeller with SAS Development Experience Location: Sydney CBD (Hybrid Working)
Job Type: 12-Month Initial Contract
We are seeking an experienced Senior Data Modeller for an initial 12-month contract with the possibility of extension.
This is an exciting opportunity for a professional with hands-on expertise in SAS development, IRB (Internal Ratings-Based) models, and credit risk modelling solutions.
If you have a strong background in model calibration and proficiency in R, this role is perfect for you.
Based in Sydney CBD, this position offers the flexibility of hybrid working.
You will be a key player in developing and optimising our advanced risk models to ensure we remain at the forefront of the industry.
Required Skills and Qualifications: Bachelor's degree in a quantitative field (e.g., Mathematics, Statistics, Computer Science, Engineering).Proven experience in credit risk modelling, with a strong understanding of IRB approaches.Extensive experience in SAS development, including programming and data manipulation.Strong skills in model calibration, validation, and performance monitoring.Proficiency in R for statistical analysis, model development, and data visualisation.Deep understanding of credit risk, regulatory standards, and industry best practices.Ability to communicate complex modelling concepts and results to non-technical stakeholders.Strong problem-solving skills and the ability to work independently as well as part of a team.Key Responsibilities: Develop and optimise advanced risk models.Experience: 3 years
Skills: Senior Data Modeller, SAS development, IRB, credit risk modelling, model calibration, R
Qualifications: Three or more years of experience in credit risk capital modelling (PD, LGD, and EAD).Advanced SAS.SQL.R.Data management expertise.Education: Bachelor Degree
At Randstad, we are passionate about providing equal employment opportunities and embracing diversity to the benefit of all.
We actively encourage applications from any background.
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