What you'll be working on
Build and own lifetime value and churn models that drive how Marketing prioritises customer segments and allocates spend across acquisition and retention channels.
Design and run incrementality experiments, randomised controlled trials and quasi-experiments, that establish whether our marketing interventions actually cause the outcomes we attribute to them, and build the standards that govern how these experiments are set up, powered and interpreted.
Develop spend-curve and scenario planning models that translate channel investment into forecasted incremental outcomes, giving commercial and marketing teams the tools to make allocation decisions with confidence.
Work directly with marketing and commercial stakeholders to frame hypotheses, design clean tests and communicate results, including the uncertainty in them, in terms non-technical audiences can act on.
Productionising models, monitor for drift and maintain reliability over time, with a clear path from prototype to production.
What we're looking for
7+ years in applied data science, statistical modelling or quantitative research, with a track record of shipping models that influenced real decisions, not just delivered analysis.
Builder mentality: you write production-quality Python or R, you care about getting things into the hands of decision-makers, and you know when a workable deployed model beats a perfect one still in development. You move quick without creating problems you cannot see.
Strong statistical modelling: regression, survival and hazard models, Bayesian inference, time series.
Comfortable with data platforms on AWS or GCP with an ability to deploy and scale batch jobs or always-on models.
Causal inference expertise: difference-in-differences, synthetic control, interrupted time series, matching methods.
Solid SQL and hands‐on experience with a cloud data warehouse (BigQuery preferred).
The ability to communicate with non-technical stakeholders clearly enough that they can act on your outputs.



Explaining the model is as important as building it.
AI-native ways of working: you use AI agents and tools as a genuine accelerator in your workflow, for analysis, code generation and data exploration. You evaluate model outputs critically, know when to push back, and are actively extending what you can do independently through agentic approaches. This is a core expectation of the role, not an optional extra.
A bonus
Experience in marketing analytics: customer LTV, media mix modelling or channel attribution in an e-commerce or subscription context.
MLOps experience: model versioning, deployment pipelines, monitoring and retraining workflows.
Familiarity with the GCP ecosystem (BigQuery, Vertex AI, Cloud Run).
Experience presenting to senior commercial stakeholders or embedding models into business planning cycles.
Background in e-commerce, subscription or retail where customer behaviour data is central to the business.
Where you'll work
This is a Sydney-based role. You will closely collaborate in-person with the Customer team. Our office is above Wynyard station, it's pet-friendly (of course), and we work flexibly, a mix of office and home, with the team typically in the office 3‐4 days a week.
A few good things
Heaps of development opportunities - lunch & learns, secondments & unlimited learning courses via Go1
Flexible working environment
Up to 50% employee discount
Product sample giveaways
Pawrental leave and wellbeing leave
Volunteer days for the causes you care about
Fitness corporate partnership
Why you'll want in
Looking after pets, and the pet parents who love them, is what gets us out of bed. That energy carries into how we work, and into what your days here would feel like.
You'll own your patch and have the room to act on it. We move fast and decide quick, and we'd rather test an idea and learn from it than sit on it. You'll have rich, real-time data at your fingertips to back your thinking, and the freedom to chase an opportunity the moment you spot one. The best idea wins, wherever it comes from.
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📌 Full Stack Data Scientist (New South Wales)
🏢 Pet Circle
📍 New South Wales