Description:
This is a Analyst Quantitative Modelling role with one of the leading companies in AU right now -- Bank of Queensland -- with an amazing team. They are continuing to grow rapidly. This is the chance to join right as the takes off.
More About the Role at Bank of Queensland
## **About the Role** Join our dynamic Risk Analytics & Modelling team as an Analyst in Quantitative Modelling at BOQ Group! In this role, you will be at the forefront of developing cutting-edge credit risk models and providing valuable insights to drive strategic decision-making. You will have the opportunity to work on exciting projects, including the development of credit risk application and behavioural scorecards, PD, LGD, and EAD models (IFRS9 or AIRB), and innovative dashboards for credit risk insights. As part of our team, you will also work on a state-of-the-art cloud platform, leveraging advanced technology to enhance model performance, streamline processes, and drive innovation in credit risk analytics. Your work will directly contribute to enhancing our digital presence and improving customer engagement. Collaborate with cross-divisional teams, legislators, regulators, and industry bodies to make a real difference. This is a unique opportunity to grow your career in a supportive and forward-thinking environment. ## **About you** We are seeking a proactive and analytically minded individual who is passionate about data and statistical models and eager to take on new challenges. You do not need to meet all the requirements; however, as the ideal candidate, you will have: - Tertiary qualifications in a technical or analytical discipline such as Actuarial Science, Data Science, Business Analytics, Econometrics, Applied Statistics, Applied Mathematics, Physics, Engineering, or Finance. - Experience in mathematical, statistical, and predictive modelling, with familiarity in different regression methods. - Hands-on experience with credit risk modelling in the banking or financial services industry (desired but not mandatory). - Proficiency in programming languages such as SAS, SQL, R, and Python, with experience in code version control tools like Git and Bitbucket. - Experience working with cloud-based analytics platforms, such as Databricks (desired but not mandatory). - Strong mathematical and statistical knowledge, with the ability to translate complex concepts into clear insights for non-technical stakeholders. - Excellent presentation and communication skills, with a collaborative and team-oriented mindset. - A self-starter attitude, with curiosity and eagerness to explore complex data and relationships.
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