Risk Modelling Development Specialist
Risk Modelling Development Specialist
About Us
At ANZ, we're shaping a world where people and communities thrive, driven by a common goal: to improve the financial wellbeing and sustainability of our millions of customers.
About the Role
As a Manager for Wholesale Models, you will be part of the GCM team in the Group Risk Metrics and Measurement (RMM) department and focus on the build and maintenance, including any remediation, of wholesale credit models that predict default risk, losses, and exposures. With the financial industry transforming and new cloud-based capabilities progress, this role will also be instrumental for transforming modelling, including moving modelling activity into the cloud, and enhancing the team’s AI capabilities.
Banking is changing and we’re changing with it, giving our people great opportunities to try new things, learn and grow. Whatever your role at ANZ, you’ll be building your future, while helping to build ours.
Role Type: Full Time, Permanent
Role Location: Manyata Tech Park, Bengaluru
What will your day look like?
- Managing and delivering modelling assignments in an autonomous manner from low to high degree of complexity according to the ANZ standards and in line with regulations applying to the various geographies of ANZ.
- Managing, engaging, and influencing stakeholders as well as maintaining a good relationship with Internal Model Validation and Model Monitoring. Acting as a thought leader and trusted advisor for all stakeholders due to subject matter expertise and proven ability to deliver value-add services.
- Supporting her/his Senior Manager in investigating new modelling techniques and required data and investigating/researching the application of latest data science developments and machine learning techniques to wholesale credit modelling. Driving change and research of new advanced modelling techniques., especially the application of latest data science developments and machine learning techniques to wholesale credit modelling.
- Presenting results in meetings and discussing results with stakeholders including model users, internal model validation, internal audit, external audit, and the broader credit modelling team, i.e., retail modelling, wholesale modelling and stress test modelling.
- Becoming a subject matter expert in the development of wholesale credit models in the cloud.
- Contributing to modelling team code libraries/packages on ANZ GitHub.
- Delivering high quality documentation.
What will you bring?
To grow and be successful in this role, you will ideally bring the following:
‘Must have’ knowledge, skills, and experiences:
- Experience with analytical packages (R, Python, SQL, Spark, Hadoop). Experience with Google Cloud (Big Query, DBT, DBT Macros). Experience with ANZ GitHub, CDSW, EBD and Hive.
- Knowledge of machine learning techniques such as XGBoost, Convolutional Neural Networks, or similar.
- 6+ years experience with (retail or wholesale) credit risk modelling (Basel A-IRB PD, LGD and EAD models) and a good understanding of credit metrics.
- Understanding of finance and the commercial environment in which credit models are used.
- Proven abilities to communicate complex subject matter with senior executives in formal and informal situations.
- Strong analytical, numerical, research and problem-solving skills. Attention to details.
- Excellent written and verbal communication.
- Ability to plan and prioritize to deliver the best outcomes.
‘Good to have’ knowledge, skills, and experiences:
- Proven project management skills.
- Experience / exposure to banking data across retail / wholesale areas.
- Ability to manage highly specialised resources.
Qualifications
Tertiary qualification in Finance, Statistics, Operations Research, Mathematics, Econometrics, Engineering, Data Science, or related field.
You’re not expected to have 100% of these skills. At ANZ a growth mindset is at the heart of our culture, so if you have most of these things in your toolbox, we’d love to hear from you.
Job Posting End Date
14/11/2025 , 11.59pm, (Melbourne Australia)