Full Stack Data Analyst/Scientist
Posted on:
September 15, 2025
Job description
As our second data hire and working closely with the head of data, you’ll play a critical role in building out the foundations of our data function.
This is a full-stack data role — you’ll spend most of your time in analytics and business intelligence (answering questions, shaping metrics, building dashboards), but you’ll also dive into upstream data modeling, light data engineering, and the occasional ML/AI project.
This isn't a Machine Learning Engineer role but it's much broader in scope than a traditional Data Analyst role with cross over into Data Science and Data Engineering.
If you like variety, ownership, and the chance to shape how data gets done at a growing company, this role is for you.
This role and our Engineering team is Sydney based with 2-3 days a week in office, in the CBD.
Responsibilities
What you’ll do
- Write clean, well-structured SQL to build analytics-ready datasets and support decision making
- Use Python or R (pandas, dplyr, etc.) to manipulate data and pull out insights
- Own problems end-to-end: from ingestion and warehouse modeling to BI dashboards and presentations
- Partner with product, ops, and clinical teams to understand needs and deliver actionable insights
- Make thoughtful trade-offs about where logic should live (app layer, warehouse, or BI layer)
- Explore and apply AI tools (RAG, LangChain, agentic workflows, Cursor/Claude Code, etc.) to accelerate analysis and pipeline work
- Document technical debt and contribute to a roadmap for scaling our data stack
Job requirements
What we’re looking for
- 2–5 years of hands-on experience in a data role (analyst, scientist, or analytics engineer) in start up or scale up environments
- Solid SQL skills (comfortable with joins, CTEs, and writing clean, reusable queries)
- Basic to intermediate Python or R (pandas, dplyr, or similar)
- An interest in working across the full stack of data — analytics first, but able to step into engineering as needed
- Curiosity about AI and modern data tooling
- A “scrappy but structured” mindset: deliver value quickly, while keeping an eye on scale and quality
Why join us
- Be the second member of the data team and help shape how we do data from the ground up
- Work across the full data lifecycle, not pigeonholed into a narrow role
- Gain exposure to a modern AI-heavy company where experimentation is encouraged
- Make a tangible impact on healthcare outcomes
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