Senior Data Scientist

Wagetap is a profitable fintech on a mission to elevate people's finances - and we're just getting started.

Over 50% of people live paycheck to paycheck without access to savings to smooth out the inevitable bumps life throws at them. Millions turn to unsustainable short-term solutions - payday loans, consumer credit or credit cards - just to get by. We're changing that. Wagetap gives people early access to up to $2,000 of their wages, helping them break the debt cycle and regain control of their finances.

We've lent over $1B to Australians, supported 250,000+ customers across 3.5M loans, and maintain a 4.9 rating on the App Store. We've done it all with a tight team of 20 across Australia & the UK. Now we're scaling globally with the US our next market.

The Role | Senior Data Scientist

Location | Sydney or Melbourne

Data Scientists at Wagetap make an enormous difference to our success. You’ll work on the systems that directly determine how we lend — who we lend to, how much, and how we manage risk. This is a highly applied role. You’ll be improving credit models, running experiments, and investigating real-world behaviour - not working on theoretical problems.. You’ll enjoy tackling a wide variety of problems with high impact - from revenue, risk, to our ability to expand into new markets.

What you’ll do

• Build, improve, and extend credit and behavioural models, from problem framing through to production
• Building models for a market with no history, drawing on what we’ve learned from our home markets & other expansion projects
• Design and run experiments - A/B tests, policy changes and causal analysis - to measure what’s actually working
• Dig into root causes when metrics move, from repayment patterns to anomalies and fraud
• Explore & extend our models to different loan tiers and develop stronger features
• Work closely with engineering to productionise, monitor and explain models
• Turn complex data into clear recommendations that shape commercial decisions

What we’re looking for

• Experience, at least 5 years. applying data science to real-world problems across analytics, modelling and experimentation
• Hands-on experience designing and running experiments (A/B tests, sample sizing, causal inference)
• Experience owning production models and monitoring performance over time
• Ability to balance model performance with commercial outcomes
• Clear communication - you can explain trade-offs and decisions to non-technical people
• Strong Python and SQL skills
• Experience with ML techniques (e.g. regression, tree-based models) and making models explainable
• Intellectual range - you’re curious, quick to learn, and comfortable going deep on problems you haven’t seen before
• Comfortable in a scrappy, build-it-yourself environment - you don’t need a big tooling stack or platform team to get things done
• Nice to haves: credit, lending or risk with high-volume behavioural data; fintech or startup experience; AWS data tools (S3, Glue, SageMaker) or AI coding tools like Claude Code

Why Wagetap

• Real scope: you'll own a broad slice of the business and shape how it runs as we scale globally
• Profitable and stable: We're 100% self reliant, which means we make considered decisions and invest in the right people
• High ownership: people here define how problems are solved
• Flexible and remote friendly: We take flexibility seriously. We work hybrid with 2 days a week in our Sydney/Melbourne CBD office.