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Posted 3 days ago

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Lead, Credit Decision Science and AI

SydneyHybridFull-time

AI Summary

Lead the analytics and AI capability within Credit Risk, overseeing a team of analysts, credit decisioning models, and the adoption of AI and automation across credit risk workflows.

About this role

Wisr is committed to building a supportive, inclusive and diverse workplace, and we strongly encourage applications from all backgrounds and identities. We’re happy to accommodate any reasonable adjustments to the interview process to ensure equal opportunity for all. If you require reasonable adjustments, please reach out to us via careers@wisr.com.au.

Our Why, What and How

We are a proudly purpose-led ASX-listed fintech on a mission to power peoples’ progress and make a real difference in the world, starting right here in Australia. By building products and experiences designed to have a positive impact on the financial health and lives of our customers, we are inching ever-closer to achieving our purpose.

We offer smarter, fairer loans that help people kick their goals sooner, a nifty round up tool to help people get out of debt and save even faster, and a dashboard that helps people track and improve their credit scores.

The better we do this, the more positive change and impact we can have on our customers. Now is the time to join one of Australia’s fastest growing fintechs and make an impact.

We are a people first business and value flexibility as part of our work - our team work in a hybrid working environment, 3 days per week in our beautiful office space.

The Role

This is a newly created role leading the analytics and AI capability within Credit Risk, Data & Analytics. You'll take on an established team of Analysts, with scope to shape the function and how it operates.

Day to day you'll oversee the team's modelling work across credit decisioning, risk-based pricing, portfolio monitoring and IFRS 9 ECL. You'll own the analytics platform, lift the team's technical maturity, and lead the adoption of AI and automation across credit risk workflows. You'll run the team's sprint priorities, mentor the team, and make sure what gets built deploys cleanly and holds up in production.

This is a hands-on leadership role. You'll set technical direction while staying on the tools.

Key Responsibilities

Platform and Capability

  • Own the analytics and modelling stack across Snowflake, Dataiku and Python.
  • Lift the team's technical maturity across version control, reproducibility, model monitoring and deployment discipline.
  • Move recurring analysis into automated, production-supported processes.
  • Set documentation, peer review and handover standards for the team.
  • AI and Automation

  • Lead the adoption of AI and GenAI tooling across credit risk workflows, including agentic and LLM-based solutions for document review, income and expense verification, portfolio commentary and reporting.
  • Responsible for the production of data products that will serve to evaluate the accuracy of AI agents, benchmarking agent decisions against actual outcomes.
  • Architect and deliver the mechanism to create AI agent self-improvement loops, owning the feedback loop that translates process changes into updated agent logic and retrained behaviour.
  • Build and own the data pipelines that ingest agent audit trails, reasoning and decisions powering ongoing accuracy monitoring and benchmarking.
  • Identify and prioritise use cases, build the business case for investment, and measure the benefit delivered.
  • Make sure AI solutions meet the model governance, validation and monitoring standards required in a regulated lending environment.
  • Modelling and Decision Science

  • Lead the development, validation, deployment and ongoing monitoring of credit decisioning, behavioural and ECL models, and the pricing and offer logic that sits alongside them.
  • Design and run test-and-learn on credit policy and pricing changes, accounting for seasoning lag in early performance reads.
  • Work with bureau data (Equifax, Illion) and with bank statement and open banking data as model inputs.
  • Delivery and Ways of Working

  • Run the team's delivery on the CRDA board in Jira: shape and size stories, groom the backlog, and set sprint priorities against competing demand from Credit, Pricing, Finance and Product.
  • Maintain the team's delivery standards, covering definition of ready, story sizing, dependency management and technical sub-tasks.
  • Work with Data Engineering, Product and Technology on shared platform dependencies and roadmap sequencing.
  • Stakeholder Engagement and Governance

  • Translate model outputs into decisions for Credit, Pricing, Collections, Product and Finance.
  • Prepare and present analytical papers to Credit Committee, Risk Committee and board audiences.
  • Maintain modelling, validation, governance and monitoring practice consistent with NCCP, RG 209 and ASIC responsible lending obligations.
  • Team Leadership

  • Lead, mentor and develop a team of analysts and data scientists.
  • Manage priorities and delivery, and maintain quality standards across the team's output.
  • About You

    Key Technical Skills

  • Strong Python and SQL.
  • Understanding of the full model lifecycle: development, deployment, monitoring, maintenance.
  • Strong background in credit risk modelling within a lending environment: credit decisioning, behavioural, pricing or ECL models.
  • Hands-on experience delivering AI or GenAI solutions into production business processes.
  • Proven experience leading or mentoring an analytics or data science team.
  • Experience running delivery in an Agile environment using Jira: backlog grooming, sprint planning, story sizing and prioritisation.
  • Confident in communicating with non-technical stakeholders and senior leadership.
  • Advantageous

  • Dataiku, Snowflake, Power BI or Tableau.
  • IFRS 9 ECL methodology and provisioning.
  • Australian consumer credit regulation: NCCP, RG 209, AFCA, privacy and credit reporting.
  • Agentic AI frameworks and LLM APIs applied to document or data-heavy workflows.
  • ML deployment.
  • Skills

    Agile DeliveryBehavioural ModellingCredit DecisioningDataikuECLGenAIIFRS 9JiraLLM APIsModel GovernanceModel MonitoringNCCPPower BIPythonRG 209SnowflakeSQLTableau

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