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Quantium

Senior Data Scientist - Product Analytics

Sydney, New South Wales, Australia +1

Location
Sydney, New South Wales, Australia · Melbourne, Victoria, Australia
Work
Not stated
Employment
Not stated
Level
Senior
Function
Data & AI
Pay
Not stated
Posted
7 weeks ago

About the role

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.

Product Analytics has embraced AI-native ways of working across our analytical workflows, and we're now moving from adoption to transformation — systematically advancing our analytical assets through an agentic maturity framework we designed ourselves.

The Role

As a Senior Data Scientist, you are analytically strong and genuinely excited about AI-native ways of working. You'll bring solid foundations in data science, Python, and SQL — and combine them with AI tools to build, transform, and scale analytics solutions.

We operate globally across Australia, India, the UK, and North America. You'll work within cross-functional teams alongside Product Leads, Delivery Managers, and engineers — taking on increased technical responsibility while developing coordination and mentoring capabilities.

How will you make an impact?

  • Design and build analytics solutions using AI-native workflows from prompt-driven exploration through to agentic code generation — and progress analytical assets along our agentic maturity framework
  • Critically evaluate AI-generated outputs and develop reusable approaches, Claude skills, and specifications that scale across teams and geographies
  • Take responsibility for significant components of analytics solutions including models, algorithms, and optimisation approaches, with attention to quality and scalability
  • Apply advanced data science methods including experimental design, feature engineering, statistical modelling across complex datasets using cloud platforms such as GCP, Azure, and AWS
  • Create detailed specifications for analytics work that engineering teams can implement, and contribute to technical discussions on approach, effort, and timelines
  • Support and coordinate technical work with analysts at different experience levels, sharing knowledge and building capability — particularly around AI-native practices
  • Identify opportunities for workflow transformation and process improvement, and support client project delivery and ongoing engagement requirements

The superpowers you’ll be bringing to the team

  • 4–7 years of experience in data science, AI/ML development, or technical consulting
  • Strong Python and SQL programming skills for complex data challenges
  • Solid understanding of data science methods: experimental design, feature engineering, statistical modelling, and model development — with practical commercial application
  • Familiarity with software engineering practices including version control, testing, documentation, and deployment workflows such as CI/CD pipelines and containerised environments
  • Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP)
  • Strong communicator — able to explain complex technical concepts clearly to non-technical audiences
  • Interest in agentic development patterns and comfort working in a team where AI-native methods are the default, not the exception
  • Strong problem-solving approach with the ability to work independently and collaboratively across diverse, distributed teams
  • Experience using AI tools (Claude, ChatGPT, GitHub Copilot, or similar) in your work or studies or a compelling demonstration of rapid learning and genuine enthusiasm
  • Strong understanding of ML/AI fundamentals including how LLMs work, transformer architectures, and when to apply different approaches

Remember – you might not tick all the boxes, but don’t let that from stopping you applying. We’re more interested in how you work, your ability to solve problems and think big.

What could your Quantium Experience look like?

Working at Quantium will allow you to challenge your imagination. You will get to solve complex problems using rigor, precision and by asking great questions – but it also means you can think big, outside the box and push your problem-solving skills to the max.

By joining the Quantium team, you’ll get to:

  • Forge your path: So many of our team have moved around different teams or offices. You’ll be in the driver’s seat, and we empower you to make your career your own.
  • Find your kind: Embrace diversity and connect with your tribe (think foodies, dog lovers, readers, or runners).
  • Make an impact: Leave your mark. Your contributions resonate, regardless of your role or rank.

But wait, there’s more!

We’ve got some pretty sweet perks:

  • Flexible work arrangements: Achieve work life balance at your own pace with hybrid and flexible work arrangements.
  • Continuous learning: Our vision is empowering analytics talent to thrive. The Analytics Community fosters the development of individuals, thought leadership and technical excellence at Quantium through building strong connections, fostering collaboration, and co-creation of best practice.
  • Remote working: Embrace the opportunity to work outside of your assigned home location for up to 30 days every year.

Apply now and let's forge a better, more intelligent world together!

Quantium’s recruitment process involves the collection and use of personal information, see our Candidate Data Collection Notice for more information. This provides information on how we collect, use & store your personal information, including potential disclosure to our majority shareholder, Woolworths Group Limited.

Source

Posted by Quantium on their own hiring page, job-boards.anz.greenhouse.io. OptiTalent shows it as published, read 07 Nov 2026 01:30 UTC; the original is the reference.

View the original ad ↗

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