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 [email protected].
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.
About the job
Our Credit Risk team is growing and we’re looking for a Credit Risk Analyst to join the team in a highly critical role. By utilising your strong analytical background, you’ll be assisting Wisr in expanding our use of data to make optimised decisions for a range of credit risk activities.
With a particular focus on reviewing, analysing and reporting on our originations and arrears management strategies, you’ll be leveraging your strong data visualisation and manipulation skills to help achieve business objectives.
What You’ll Do
• Work closely with cross functional teams on the continual improvement of originations and arrears management strategies using data and analytics
• Maintain and improve a suite of comprehensive credit risk reports for senior management in order to support business objectives
• Assist in the creation and maintenance of auto-decisioning, collections segmentation, risk-based pricing and other predictive models
• Review and update credit risk policies and procedures to ensure alignment with evolving market conditions and regulatory changes
• Maintain accurate and up-to-date documentation of credit risk assessments, decisions, and actions taken
• Stay abreast of industry trends, market developments, analytics, AI and regulatory changes impacting credit risk management
What success looks like in 6 months
• You are embedded in the Credit Risk team - you have a strong working understanding of Wisr's originations and arrears management strategies, and the team relies on you to deliver accurate, timely analysis and reporting with minimal oversight.
• Your analytical contribution is evident - you are maintaining and actively improving Wisr's suite of credit risk reports, and have identified at least one meaningful enhancement to how we monitor originations or arrears performance that is in progress or already delivered.
• You have contributed to the improvement of KPI’s and your work is visibly supporting the team's ability to respond to portfolio trends, market conditions and regulatory requirements.
About you
With a strong analytical mindset and ability to think long term, you thrive in a fast paced working environment where each day differs from the last. You will have gained your experience within financial services or similar and are looking to take on a challenge with a growing team and business. You’ll also have:
• Tertiary qualification in a Technical, analytical or mathematical discipline or equivalent
• Ideally some experience in a similar role within the financial services industry, telco or utilities
• Good knowledge of Credit Risk and/or Quantitative analytical skills such as knowledge of credit score development and implementation
• Experience with data manipulation and data visualisation tools such as SQL, SAS, Alteryx, Tableau, Power BI, R or Python