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.
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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 explicit 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.
#J-*****-Ljbffr

📌 Senior Data Scientist (Melbourne)
🏢 Wagetap
📍 Melbourne