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

The Manager position with the Credit Model Validation and Insights (CMVI) team at ANZ is primarily responsible to validate a diverse suite of credit risk models for Wholesale (non-retail) and Retail portfolios and to support the development of validation methodologies/frameworks, tools, and related governance activities. The successful candidate is expected to provide guidance and coaching to junior staff and be self-sufficient in completing model validations autonomously.

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 you bring?

Essential skills:

• Strong foundation in Mathematics/Statistics/Quant skills
• Proficiency in at least two quantitatively focused programming languages: e.g. R, Python, Julia, MATLAB, SAS
• Strong data manipulation/management skills including SQL and working with databases (e.g. BigQuery, SQLServer)

Relevant Experiences:

• Experience in leading building/validating credit risk models (e.g., capital/AIRB, provisions/IFRS9 ECL, decisions/scorecard models, or Stress Testing models).
• Knowledge of Basel regulatory framework, capital (incl. PD, LGD, EAD) models, ECL/IFRS9, and stress testing
• Knowledge of Wholesale (non-retail) models and portfolios.

Soft Skills:

• Be able to independently lead model validation/development project with small project teams
• Be Curiosity driven
• Lifelong learner with a growth mindset with a demonstrated ability to learn technical and soft skills on the job
• Collaborate well within a team environment
• Proficient written and verbal communication
• Problem solving skills and attention to detail
• Engage with internal and external stakeholders effectively

Educational Background: Post graduate qualifications in statistics, econometrics, mathematics, data science, machine learning or equivalently quantitative field

Desired Skills:

• Experience in R/R Shiny, Git/Github
• Experience with machine learning techniques such as XGBoost, Neural Networks

So why join us?

From the moment you join ANZ, you'll be doing meaningful work that will shape a world where people and communities thrive.

But it's not just our customers who'll feel your impact. you'll feel it too. Because at ANZ, you'll have the resources, opportunities, and support you need to take the next big step in your career.

We're a diverse bunch at ANZ in different roles, different locations, doing different things. That's why we have a range of flexible working arrangements, so our people can 'make work, work for them'. We also provide a range of benefits including access to health and wellbeing services and discounts on selected products and services from ANZ and more.

At ANZ, you'll be part of an organisation where the different backgrounds, perspectives and life experiences of our people are celebrated. That's because we're committed to building a workplace that reflects the diversity of the communities we serve. We welcome applications from everyone and encourage you to talk to us about any adjustments you may require to our recruitment process or the role itself. If you are a candidate with a disability or access requirement, let us know how we can provide you with additional support.

To find out more about working at ANZ, visit https://www.anz.com.au/careers. You can apply for this role by visiting ANZ Careers and searching for reference number 88241.

Job Posting End Date

28/02/2025 , 11.59pm, (Melbourne Australia)