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Sydney, New South Wales, Australia
Hybrid
Who is Shift?
Shift provides business finance to small, established and corporate sized businesses in Australia, including Business Overdraft, Equipment Line, Asset Finance, Term Loan and Trade Account. Founded in 2014, Shift has funded more than 30,000 Australian businesses.
At Shift, our unique approach to product innovation combined with our collaborative culture means you can build your career in a supportive environment. You’ll be joining a diverse team of over 300 people who are always looking to deliver better outcomes for Australian businesses.
About the role:
We’re building the credit risk model platform behind every lending decision at Shift. The goal is an always-on, confidence-rated view of risk for every customer, served straight to our Credit Decision Engine so models can make credit calls automatically and our people can focus on customers. Our team has deep statistical and research strength. What we need now is someone with real engineering rigour to take our models from prototype to production and make them scale. You’ll build predictive models and the deployment layer they run on. We use AI heavily in how we work: Claude sits beside us for coding and deployment, and Copilot helps review our PRs.
What you’ll do:
Build and deploy machine learning models that predict credit risk (PD, LGD, EAD and expected loss), including how different types of security change our loss exposure
Turn our prototype model deployment layer into something scalable: versioned, monitored and reliable enough for automated decisions
Make sure every model can be trusted in production, with monitoring, data validation and documentation, so no model depends on the person who built it
Bring in new data sources, including customer insights from our AI-powered Customer Knowledge Engine
Lead projects from start to finish, then pass the knowledge on and lift the team’s engineering standards along the way
Work with Credit, Product, Risk and Technology to agree what the models need to deliver and explain the results in plain language
What you’ll bring:
5+ years building predictive models in a business setting, with a track record of getting them into production and keeping them there
Strong Python and SQL, with solid engineering habits: version control, CI/CD, testing and code review
Hands-on experience building model services or APIs, including serving, versioning and monitoring
Experience with Databricks or another distributed computing environment
A solid statistical foundation, including how to measure how confident a model is in its predictions
Experience in credit risk, lending or financial services is a plus, but not essential
The ability to explain complex work simply to senior stakeholders
Curiosity about using AI to work smarter, and the habit of fixing problems properly instead of patching them
Key benefits:
Hybrid working: we’re headquartered in North Sydney with state-based workplaces and offer a hybrid work policy. Our offices have spaces for collaboration, socialising and focused work.
Parental leave: up to 26 weeks paid.
Strategy Week: twice a year the whole team comes together to hear the business strategy and product and technology roadmap first-hand, with fortnightly all-company business updates in between.
Flat structure: everyone can learn from each other and senior leaders across the business.
Wellbeing: benefits supporting your physical, psychological and financial wellbeing, from a day off on your birthday to end of trip facilities.
Additional information:
If you don’t meet all the qualifications or skills but think you’d be a great fit, please apply anyway.
Learn more about working at Shift at shift.com.au/careers.
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