Analysis and estimation of the drivers of credit risk of ANZ s wholesale customers according to internal standards and regulatory requirements. Assessing the impact of these drivers on the capital position of ANZ. Understanding and supporting the model lifecycle end to end.

• Assessment of emerging risks on the various portfolios, geographies, and business units within ANZ.
• Building models that accurately estimate the credit risk of ANZ s wholesale customers. Ensuring all services delivered comply with ANZ Group Risk strategy, policies, processes and standards and with external regulatory requirements.
• Engaging stakeholders and participating in discussions with Internal Model Validation and Model Monitoring.
• Supporting her/his 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.
• Presenting results in meetings and discussing results with stakeholders including model users, internal model validation, and the broader credit modelling team, i.e., retail modelling, wholesale modelling and stress test modelling.
• Growing into a subject matter expert in the development of credit risk models.
• Contributing to modelling team code libraries/packages on ANZ GitHub.

What will you bring

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

The must have knowledge, skill and experience (KSE) the role requires are:

• Experience with analytical packages (R, Python, SQL, SAS).
• At least 2 years of experience with (retail or wholesale) credit risk modelling and a good understanding of credit metrics.
• Basic understanding of finance and the commercial environment in which credit models are used.
• Strong analytical, numerical, and research skills. Attention to details.
• Able to work under tight schedules and consistently meet objectives.
• Good written and verbal communication. Ability to present results in meetings and discuss results with stakeholders.

The good to have knowledge, skill and experience (KSE) the role requires are:

• Cloud computing and data skills.
• Experience / exposure to banking data across retail / wholesale areas.
• Knowledge of machine learning techniques.

Qualifications

• Tertiary qualification in Finance, Statistics, Operations Research, Mathematics, Econometrics, Engineering, Data Science, or related field.

Role: Analytics Consultant

Industry Type: Banking

Department: Data Science & Analytics

Employment Type: Full Time, Permanent

Role Category: Business Intelligence & Analytics

Education

UG: Any Graduate

PG: Any Postgraduate

About company

ANZ Bengaluru began its journey 34 years ago in 1989 and is critical to the delivery of ANZ’s operations and strategy. Well established in Bengaluru, we are the largest Banking Operations and Technology Capability Centre of ANZ outside Australia with more than 7,500 full-time employees.

We provide banking operations services like Retail, Commercial and Institutional banking, Trade Finance, and Technology. We also specialise in the areas of Economic Research, Risk Analytics, Client Insights, and Credit Decisioning.