Lead Analyst - Product Analytics

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).

Product Analytics is leading Quantium’s AI transformation. Our 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 leadership role for someone ready to develop both people and AI-native analytics capability. You’ll coordinate a team of analysts, guide them through technical and AI transformation challenges, and maintain your own technical involvement — all while growing your management skills in a collaborative, supportive environment.

The Product Analytics team operates globally across Australia, India, the UK, and North America. You’ll work across geographies and functions, helping your team deliver high-quality analytics outcomes while actively driving the AI transformation of your domain’s workflows and assets.

How You’ll Create Impact

Lead AI Transformation

• Drive the AI transformation of analytical assets and workflows within your domain, setting targets on our agentic maturity framework and holding the team accountable to progress
• Model AI-native ways of working — using AI tools in your own work and coaching your team to do the same with increasing sophistication
• Make judgement calls on where AI adds value and where human expertise must lead, building this critical thinking capability across your team
• Contribute to shaping our Agentic Development Framework, bringing practical experience from your domain to inform what works at scale

Team Development & Collaboration

• Coordinate analytics projects and support individual growth — helping each team member build both technical depth and AI-native capability
• Collaborate on setting goals, providing feedback, and identifying development opportunities that align with the evolving capability requirements
• Create an environment where team members feel supported to experiment with AI, learn from what doesn’t work, and share what does
• Connect team members across different time zones, working styles, and experience levels

Technical Coordination & Strategy

• Coordinate the development of analytics solutions across product initiatives, ensuring quality and consistency in technical approaches
• Stay connected to technical work while developing strategic thinking about team capabilities and the AI maturity of your assets
• Support the adoption of new tools, methods, and agentic practices — helping your team move beyond basic AI usage toward workflow transformation
• Contribute to technical decisions with input from your team and leadership

Cross-Functional Partnership

• Collaborate with Product, Engineering, and other teams to understand needs and priorities
• Translate between technical work and business requirements — increasingly framing analytics capability in terms of AI-native delivery and measurable impact
• Work with other Analytics Leads to share approaches, coordinate AI transformation efforts, and avoid duplicating work across domains
• Contribute to planning and estimation processes, factoring in the efficiency gains from AI-native methods

The Superpowers You’ll Be Bringing To The Team

Technical credibility: 7+ years in data science or analytics, with strong Python and SQL skills and solid experience with GCP and cloud-based analytics tools. You understand the work your team does because you’ve done it yourself.

AI-native leadership: Active experience with AI coding and analytics tools — comfortable enough to coach others, not just use the tools yourself. You have a clear vision for how AI transforms analytical work, not just makes existing processes faster.

People focus: A genuine interest in helping others grow. You don’t need to have managed a team before — but you’re ready to step into that space, develop your leadership style, and bring your team along on the AI transformation journey.

Adaptability: Comfortable navigating a rapidly changing technical environment. You can balance hands-on technical work with team coordination, and you approach the pace of AI evolution with curiosity rather than anxiety.

Required Experience And Capabilities

• 7+ years of experience in data science or analytics roles, with readiness to take on coordination and leadership responsibilities
• Strong experience with Python and SQL for data analysis and solution development
• Good experience with Google Cloud Platform (GCP) and cloud-based analytics tools
• Solid understanding of data science methods, statistical approaches, and their practical application in commercial contexts
• Active experience using AI coding and analytics tools (Claude, Claude Code, GitHub Copilot, ChatGPT, or similar) — comfortable enough to coach others
• Demonstrated ability to critically assess AI-generated outputs and make sound judgement calls about when AI adds value versus when human expertise must lead
• Interest in or understanding of agentic development patterns — building workflows where AI executes multi-step tasks with human oversight
• Good communication and collaboration skills across cultures, time zones, and experience levels
• Degree in engineering, mathematics, statistics, computer science, physics, or a related quantitative field — or equivalent demonstrated capability

Desirable

• Experience mentoring, training, or leading teams — formal or informal&l