• Develop, implement, and continuously improve an end-to-end model governance framework• Establish and maintain a comprehensive model inventory• Develop and implement model lifecycle management covering conceptualization, development, validation, implementation, monitoring, and decommissioning• Work with Data Governance, Product teams, Model Development, and Data Asset Managers• Provide guidance and training on model governance policies, procedures, and best practices• Champion a strong model governance culture• Identify, assess, and monitor model risks and establish mitigating controls• Ensure compliance with internal policies, APRA, BCBS 239, industry regulations, and audit requirements• Facilitate internal and external model audits and address findings and recommendations• Oversee independent model validation• Establish and manage model performance monitoring, including performance, stability, and data quality reporting• Define and track KPIs and KRIs for model governance effectiveness• Ensure comprehensive model documentation covering purpose, assumptions, limitations, data sources, and methodologies• Prepare model risk and governance status updates for senior management, governance groups, steering committees, and councils• Mentor and guide junior resources and align cross-functional Equifax teamsRequirementsBachelor's degree in a quantitative field such as Finance, Mathematics, Statistics, Economics, Computer Science, or a related disciplineMinimum 7–10 years of experience in model risk management, model governance, or model validation within a financial institution or highly regulated industryMinimum 5–10+ years of experience in data science techniquesDeep understanding of credit risk modelling techniquesIdeally,



specific data science model development experience across the credit lifecycleDemonstrated experience developing and implementing model governance frameworksStrong understanding of regulatory requirements related to model risk managementExcellent analytical and problem-solving skills with strong attention to detailSolid understanding of model types including credit risk, market risk, operational risk, ALM, and pricing modelsProficiency in data analysis tools and programming languages such as Python, R, or SAS is a plusExceptional communication, interpersonal, and presentation skillsStrong project management and organisational skills, with ability to manage multiple priorities and deadlinesAbility to work independently and as part of a team in a fast‐paced environmentData governance certifications are an advantageExperience in Credit Risk roles in Banking, Finance, Telco, or Utility sectors is advantageousExperience in analytics and Responsible AI implementation and solutionsExperience mentoring or leading teams of model and data governance specialists or managersExperience dealing with internal senior executives and external regulatorsCore CompetenciesDemonstrates expertise in developing and implementing model governance frameworks, ensuring compliance with regulatory requirements, and managing model risk within financial institutions.
Proficient in data analysis and model validation, with robust leadership and mentoring capabilities.Highest-signal resume keywordsModel Governance Framework DevelopmentModel Risk ManagementCredit Risk Modelling TechniquesData Analysis Tools (Python, R, SAS)Regulatory Compliance (APRA, BCBS 239)ATS Optimization KeywordsHard SkillsModel Lifecycle ManagementModel Performance MonitoringModel ValidationData Quality ReportingKPI and KRI TrackingModel DocumentationData Science TechniquesCredit Risk ModellingAnalytical SkillsProblem-Solving SkillsSoft SkillsCommunication SkillsInterpersonal SkillsPresentation SkillsProject Management SkillsOrganizational SkillsCertifications & QualificationsData Governance CertificationsIndustry KeywordsFinancial InstitutionHighly Regulated IndustryCredit RiskMarket RiskOperational RiskALMPricing ModelsAnalyticsResponsible AIModel Audits
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📌 Head Of Model Governance (Melbourne)
🏢 Jobtailor
📍 Melbourne