Description
Who is Quantium?
Quantium is a world leader in data science and artificial intelligence. Established in Australia in 2002, Quantium is a global team of more than 1,200 people across 14 locations with a unique blend of capabilities across product and consulting services to help businesses unlock value from data and analytics. Quantium partners with the world's largest corporations to forge a better, more intelligent world.
We're ALL in on AI — transforming ourselves into an AI-native organisation while helping our clients do the same. With 23 years of domain expertise, proprietary data partnerships, and industry-leading AI adoption (90% weekly active usage), we are at the forefront of what's possible with data.
About the team
Our Health vertical works with a wide range of Health clients in Australia and internationally — spanning health insurers, pharmaceutical companies, hospitals, and government — helping them unlock actionable insights that improve outcomes for patients and the broader community.
As a Data Scientist in the Health vertical, you'll be a collaborative technical contributor working within cross-functional teams alongside senior data scientists, consultants, and client stakeholders. You'll deepen your expertise in statistical modelling, machine learning, and AI-native workflows, while engaging directly with clients across multiple health engagements simultaneously.
How you'll create impact
- Execute high-quality analysis and deliverables across one or more health client projects simultaneously, managing your own workload and prioritisation to meet agreed deadlines
- Design and build statistical models and machine learning solutions to address health client challenges — such as predicting patient risk, modelling health behaviours, or evaluating intervention outcomes
- Apply AI tools daily to enhance your analytical workflows, moving from AI assistance through to more sophisticated agentic approaches over time
- Develop the skill of critically evaluating AI-generated outputs — learning when to trust, refine, or override
- Analyse large, complex health datasets to surface meaningful patterns and actionable insights
- Create clear, visually compelling dashboards and reports that communicate findings to both technical and non-technical audiences
- Engage directly with day-to-day client contacts — responding proactively, seeking out information needed to progress work, and building trusted relationships
- Support and mentor peers and graduates within your project streams to help the broader team achieve its goals
- Contribute to business development activities, including supporting proposals and organic growth with existing clients
The superpowers you'll be bringing to the team
Technical foundation: Solid Python/R with a strong understanding of data science fundamentals — statistical modelling, machine learning, data preparation, and validation — and a genuine commitment to delivering accurate, error-free analytical work. Experience with cloud platforms (Azure, AWS, or GCP) is valued as we increasingly deploy solutions in cloud environments.
AI curiosity: Experience using AI tools (Claude, ChatGPT, Copilot, or similar) in your work — or genuine enthusiasm and a clear willingness to build that fluency. You're open to working in a team where AI-native methods are the default.
Analytical thinking: A systematic approach to problem-solving with the ability to understand health business challenges and translate them into rigorous technical solutions — and to make the complex simple for client audiences.
Collaborative spirit: Good communication skills for working with diverse teams and clients, with the self-awareness to manage your own workload independently while knowing when to escalate or ask for support.
Required experience and capabilities
- Approximately 2–5 years of experience in data science, analytics, or a similar quantitative role
- Solid experience with Python/R for data analysis and manipulation
- Hands-on experience building and deploying machine learning models in a professional context
- Demonstrated ability to deliver accurate, error-free work to agreed quality standards and deadlines
- Strong communication skills with experience presenting findings to non-technical stakeholders
- Comfortable working across multiple projects simultaneously with strong personal organisation
- Experience using AI tools in your analytical workflows — or genuine enthusiasm and a clear willingness to develop this capability
- Tertiary qualifications in engineering, mathematics, actuarial studies, statistics, data science, business, economics, epidemiology, biostatistics, public health, or a related discipline with strong analytical focus.
Highly beneficial, but not essential
- Familiarity with the health sector — including health insurance, pharmaceuticals, hospital systems, or government health — and relevant industry terminology
- Experience building or experimenting with AI-assisted analytical workflows or prompt engineering
- Experience with data visualisation tools such as Tableau or Power BI
- Familiarity with cloud platforms such as AWS, GCP, or Azure
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