Ray White→
Lending Product Data Manager
Melbourne, Victoria, AU
Not listed
Not specified
Today
Skills
Job Description
About the role:
Are you ready to lead the charge in defining data excellence for the Australian and New Zealand lending landscapes? We are seeking a visionary Lending Product Data Manager to own, innovate, and master our comprehensive repository of lending and insurance data.
In this critical leadership role, you won't just manage data—you will become the Subject Matter Expert (SME) for all things related to Residential, Commercial, Asset Finance, with scope to expand to insurance products in future. With a view to build a team of 2-3 specialists over time, you'll be leveraging cutting-edge AI tools to ensure our data isn't just accurate, but the gold standard in the market. If you thrive on building strategic relationships and have a passion for technical precision and AI-driven efficiency, this is your opportunity to make a definitive impact.
Duties and Responsibilities:
- Acquisition & Maintenance: Drive the end-to-end process of acquiring and maintaining real-time data across all lenders and insurance providers in Australia and New Zealand. Understands that lender data is often inaccurate at source and knows how to verify and challenge it
- Product Depth: Maintain an exhaustive repository covering rates, Loan-to-Value Ratios (LVR), fees, and granular product variances.
- Policy Intelligence: Develop and maintain a deep-dive understanding of lender policies, translating complex criteria into actionable insights for brokers and consumers.
- Serviceability & Quoting: Master the mechanics of lending serviceability, quoting engines, and specific product terms to ensure accuracy in output. Ability to translate lender worksheet structures into an internal data model
- Team Management: Lead, mentor, and develop a team of 2-3 direct reports over time, ensuring the highest levels of data integrity and operational excellence.
- Stakeholder Engagement: Build and nurture high-level relationships with product and pricing teams at major and boutique lending/insurance institutions.
- Subject Matter Expertise: Serve as the internal and external SME for product data, providing guidance on market trends and policy shifts for current and future business/ tech projects where lending product data is at core Understanding of lender-specific serviceability calculators
- AI Integration: Identify and implement AI-driven tools and workflows to automate data extraction, validation, and maintenance.
- Data Auditing: Establish and oversee a rigorous audit schedule to ensure our data remains the most accurate and up-to-date in the market at all times.
Skills and Experience Required
Essential Skills:
- Domain Expertise: Extensive experience in the Australian/New Zealand lending market (Residential, Commercial, Asset Finance, or Insurance), understanding and interpreting Lending Policy
- Technical Data Foundation: Proven background as a Credit Analyst or Operational Data Engineer or Brokerage office, with established knowledge of the lending industry context and data repository best practices.
- Analytical Rigor: Exceptional attention to detail with the ability to synthesise complex policy documents into structured data.
- Leadership: Proven track record of managing a team and driving a culture of accuracy and accountability.
- Communication & Influence: Ability to influence and negotiate with external marketing, pricing and product teams at a senior level. Ideally have some existing lender relationships.
Desired Skills (The "Bonus" Points):
- AI & Automation: Experience using AI tools (e.g., LLMs, OCR, or automated data scrapers) to enhance data management processes & assist with restructuring lender policy for RAG-optimised ingestion
- Technical Proficiency: Familiarity with data visualisation tools or database management systems. Experience with product data mapping into CRMs or aggregator platforms. Experience interpreting and replicating lender serviceability calculators.
- Strategic Thinking: Ability to foresee market changes and adjust data acquisition strategies proactively.