Senior Analyst - Product Analytics

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. 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). The Product Analytics team 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. Our team operates across three domains: Retail Products - Building, transforming, and operating Quantium's global flagship analytics products including Q.Checkout and Q.Scan AI Client - Embedding with clients to deliver transformational AI programmes, bringing Quantium's analytics and AI capability directly into partner organisations AI Enablement - Rethinking how we operate as an analytics function, driving the tools, frameworks, and practices that make AI-native delivery the default This is a Senior Analyst role for someone who is 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. You won't just use AI on the side. It's how we work. 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 You'll Create Impact AI-Native Analytics Design and build analytics solutions using AI-native workflows - from prompt-driven exploration through to agentic code generation and review Progress analytical assets and workflows along our agentic maturity framework, moving them from manual processes toward context-aware and agentic delivery Critically evaluate AI-generated outputs - knowing when to trust, refine, or override is as important as knowing how to prompt Develop reusable analytics approaches, Claude skills, and specifications that scale across teams and geographies Technical Contribution Take responsibility for significant components of analytics solutions including models, algorithms, and optimisation approaches Work with complex datasets using cloud platforms (GCP, BigQuery) and modern data engineering tools Apply data science methods - experimental design, feature engineering, statistical modelling - with attention to quality and scalability Create detailed specifications for analytics work that engineering teams can implement Collaboration & Growing Influence Support and coordinate technical work with analysts at different experience levels Share knowledge and contribute to capability development - particularly around AI-native practices Contribute to technical discussions on approach, effort estimates, and timelines Help identify opportunities for workflow transformation and process improvement Support product roadmap delivery and ongoing operational requirements The Superpowers You'll Be Bringing To The Team Technical depth: 4-7 years of hands-on experience in data science or analytics, with strong Python and SQL skills and solid understanding of data science methods including experimental design, feature engineering, and model development. AI-native mindset: Active experience with AI coding and analytics tools (Claude, Claude Code, GitHub Copilot, or similar), with the critical thinking to assess AI-generated outputs and the curiosity to push into agentic development patterns. Cloud and engineering foundations: Comfortable working with GCP, BigQuery, and modern data engineering tools, with familiarity in software engineering practices including version control, testing, and deployment workflows. Collaborative drive: A strong communicator who works well across cultures and time zones, is willing to support and mentor peers, and brings genuine curiosity about how AI is changing the way analytical work gets done. Required Experience And Capabilities We don't e

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