Senior Risk Analytics & Modelling Leader

Hyundai Capital Australia Pty; Sydney; Hybrid; AUD 150,000 - 210,000; Full time

Benefits offered by this job

Hybrid work

Well Core Platinum office

Base salary & bonus

Employee Assistance Program

Parental leave 14 weeks

Car benefit scheme

Job summary

Hyundai Capital Australia is seeking a Risk Analytics & Modelling Manager to lead data-driven decision making across credit risk and residual value risk. You will drive portfolio data management, pricing, forecasting and provisioning while partnering with Risk Modelling Senior Manager.

The ideal candidate blends strong analytics with a proactive, collaborative mindset and a willingness to learn. Prior modelling experience is desirable but not essential; relevant data skills are valued.

Qualifications

• Experience in financial services, risk analytics, data science or related fields.
• Knowledge of IFRS 9, Expected Credit Loss (ECL), PD, LGD or pricing analytics advantageous.
• Experience with large datasets and turning insights into business outcomes.

Responsibilities

• Develop, monitor and enhance credit risk and residual value models.
• Prepare risk dashboards, portfolio analytics and management reporting.
• Manage data cleansing and data provision for analytics and modelling.
• Support pricing updates and monthly loss provisioning.
• Coordinate with IT to ensure data availability in core systems and data warehouse.

Skills

Python/R

SQL

Data analytics

Stakeholder management

Communication

Problem solving

Machine Learning

AI-driven decisioning

Job description

Hyundai Capital Australia is seeking a Risk Analytics & Modelling Manager to lead data-driven decision making across credit risk and residual value risk. You will drive portfolio data management, pricing, forecasting and provisioning while partnering with Risk Modelling Senior Manager.

The ideal candidate blends strong analytics with a proactive, collaborative mindset and a willingness to learn. Prior modelling experience is desirable but not essential; relevant data skills are valued.