Data Analytics Lead
3 weeks ago
Job Title: Data Analytics Lead - Retail Credit Strategy
About the Role:
This is a pivotal position in our organisation where you will play a crucial role in driving data-driven decision making for retail credit portfolios. As a key member of our team, you will be responsible for developing and implementing robust analytics frameworks to support timely forecasting of profit and loss credit metrics and balance sheet metrics.
Your primary focus will be on executing credit risk stress testing for ANZ's retail portfolios to ensure compliance with Industry-Wide Stress Tests and Group ICAAP requirements. Additionally, you will need to forecast credit provisions and risk-weighted assets for retail portfolios to inform financial planning and risk management strategies.
Key Responsibilities:
- Developing and maintaining advanced analytics models for credit risk stress testing and forecasting.
- Collaborating with stakeholders to design and implement data warehousing solutions to support large-scale data analysis and storage requirements.
- Maintaining up-to-date knowledge of macroeconomic variables and analysis, climate risk, and ESG factors impacting credit risk.
- Providing regular insights and recommendations to senior leadership on risk management and strategic business decisions.
Requirements:
To succeed in this role, you will require:
- Extensive experience in data analytics, credit modeling, and forecasting.
- Advanced knowledge of data visualization tools and programming languages (e.g., Python, R).
- Familiarity with cloud-based data platforms (e.g., Google Cloud, AWS) and data warehousing solutions.
- A strong understanding of risk management principles and practices.
What We Offer:
We offer a competitive salary package of $120,000 - $180,000 per annum, along with access to professional development opportunities, flexible working arrangements, and a range of employee benefits.
We value diversity and inclusion in the workplace and welcome applications from talented individuals from diverse backgrounds.
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