Lead Analyst

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

Drive new modelling techniques and research latest data science developments/machine learning techniques for credit risk model development and credit stress testing for retail and wholesale banking portfolios
 

Keep up to date with latest developments in Econometric techniques and apply it for credit risk modelling and credit stress testing model development
 

Implement diverse range of credit risk modelling and methodology solutions
Join a team that values collaboration and innovation!

Role Location: Campus 5A, RMZ Ecoworld, Bengaluru, 560103
Role Type: Permanent, Full-time
 

What will your day look like?

As Lead Analyst, you will be responsible for analysing the credit risk on ANZ’s wholesale and retail customers by developing credit risk models, including the prediction of default risk (PD), losses (LGD), exposures as well as credit stress testing models, and IFRS9 provisioning models in order to have correct assessment of the bank’s capital and to meet business and regulatory requirements. You could also be involved in coming up with the methodologies for credit risk model development, stress testing and climate risk modelling.

You will be accountable for the management and delivery of modelling projects from low to high degree of complexity according to the ANZ standards and in line with regulations applying to the various geographies of ANZ.
 
Keeping up to date with the latest developments in Econometric techniques and application of the same is crucial to the successful execution of the responsibilities under this role.
 

What will you bring?

To grow and be successful in this role, you will ideally bring the following:

• Be one of the go-to team members for queries on (and application of) Statistical and Econometric concepts
• Able to come up with appropriate (and practical) Statistical and Econometric techniques to solve analytical problems
• Able to simplify the application of complex Statistical and Econometric concepts for the broader team
• Keep abreast of the latest development in the application of Statistical and Econometric concepts, AI/ML techniques in the credit risk domain by going through different published papers, e.g. by various regulatory bodies and research organizations, and training
• Bring-in automation and efficiency in existing model development process using tools such as R, Python, SQL, SAS, VBA
• Have an eye for details
• Possess good interpersonal skill and communication skill

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 79535.

Job Posting End Date

21/10/2024 , 11.59pm, (Melbourne Australia)