Job Description
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Identify opportunities to simplify policy, improve business rules, strengthen automation outcomes and reduce unnecessary manual intervention
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Review credit policies, processes and business rules to improve automated decisioning outcomes
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Translate analytical findings into practical policy and operational improvements
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Support decision engine and business rule optimisation initiatives
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Collaborate with analysts to identify trends, bottlenecks and root causes within application journeys
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Prepare recommendations and implementation plans for key stakeholders
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Assess customer, risk and operational impacts of proposed changes
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Support delivery of automation and process improvement initiatives
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Monitor outcomes and identify further opportunities to improve performance
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Partner with stakeholders across Credit Risk, Analytics, Operations, Product and Technology
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Requirements
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Experience within mortgage lending, credit risk, lending policy, credit assessment or credit strategy
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Understanding of responsible lending obligations and credit risk frameworks
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Experience developing or implementing lending policies, operational processes or business rules
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Ability to influence stakeholders and drive outcome-focused change
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Experience working within decision engine, credit decisioning or automated lending environments
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Hands-on experience using tools such as SQL, SAS, Python, R, Tableau, Power BI and AI tools
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Understanding of business rules frameworks and policy translation into system-based outcomes
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Exposure to workflow automation and operational process improvement initiatives
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Experience with credit strategy systems, decisioning tools or lending technology platforms
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Understanding of data architecture concepts and data flows that support credit decisions
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Familiarity with advanced analytics techniques and performance analysis methodologies
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Exposure to machine learning,



predictive models or AI-supported decisioning environments
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Experience using process mining, operational analytics or root-cause analysis techniques
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Ability to translate analytical insights into policy, process and customer outcomes
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Degree qualification in Finance, Economics, Statistics, Mathematics, Data Analytics, Business, Risk Management, Information Systems or a related discipline is desirable
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Relevant industry certifications, lending qualifications or analytics-related credentials will be highly regarded
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Core Competencies
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Demonstrates expertise in credit risk analysis, lending policy development, and process improvement initiatives, with a solid ability to translate analytical insights into actionable business outcomes. Proficient in utilizing advanced analytics and decisioning tools to optimize automated lending environments and enhance operational efficiency.
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Highest-signal resume keywords
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Credit Risk Analysis
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Lending Policy Development
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Decision Engine Optimization
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SQL Proficiency
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Stakeholder Influence
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Hard Skills
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Credit Risk
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Lending Policy
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Business Rules Development
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Data Architecture
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Process Improvement
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Root-cause Analysis
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Predictive Modeling
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Operational Analytics
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Automation
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Advanced Analytics
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Soft Skills
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Stakeholder Management
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Influencing Change
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Collaboration
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Analytical Thinking
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Communication
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Certifications & Qualifications
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Relevant Industry Certifications
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Lending Qualifications
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Analytics-Related Credentials
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Industry Keywords
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Mortgage Lending
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Credit Assessment
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Responsible Lending Obligations
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Credit Risk Frameworks
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Automated Lending
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Business Rules Frameworks
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Data Flows
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Performance Analysis
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Machine Learning
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Predictive Models
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Tools & Technologies
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SQL
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SAS
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Python
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R
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Tableau
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Power BI
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AI Tools
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Decisioning Tools
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Credit Strategy Systems
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Workflow Automation
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📌 Manager - Home Lending Credit Risk Automation (New South Wales)
🏢 Jobtailor
📍 New South Wales