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About the Role

This is a Senior Analyst role for someone analytically strong and excited about AI-native ways of working. You will bring solid foundations in data science, Python, and SQL, combining them with AI tools to build, transform, and scale analytics solutions. You will work within cross-functional teams, taking on increased technical responsibility while developing coordination and mentoring capabilities.

Responsibilities

• 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.
• Develop reusable analytics 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.
• Work with complex datasets using cloud platforms (GCP, BigQuery) and modern data engineering tools.
• Apply data science methods, including experimental design, feature engineering, and statistical modelling, with attention to quality and scalability.
• Create detailed specifications for analytics work that engineering teams can implement.
• 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.

Requirements

• 4–7 years of hands-on experience in data science or analytics.
• Strong Python and SQL skills.
• Solid understanding of data science methods including experimental design, feature engineering, and model development.
• Active experience with AI coding and analytics tools (Claude, Claude Code, GitHub Copilot, or similar).
• Critical thinking to assess AI-generated outputs.
• Curiosity to push into agentic development patterns.
• Comfortable working with GCP, BigQuery, and modern data engineering tools.
• Familiarity in software engineering practices including version control, testing, and deployment workflows.
• Strong communicator who works well across cultures and time zones.
• Willingness to support and mentor peers.
• Genuine curiosity about how AI is changing the way analytical work gets done.
• 4–7 years of experience in data science, analytics, or similar technical roles.
• Strong proficiency in Python and SQL with experience handling complex data challenges.
• Good experience with Google Cloud Platform (GCP) and cloud-based data processing.
• Solid understanding of data science methods including experimental design, feature engineering, and model development.
• Familiarity with statistical modelling and its practical application in commercial contexts.
• Familiarity with software engineering practices including version control, testing, documentation, and deployment workflows (e.g. CI/CD pipelines, Docker).
• Active experience using AI coding and analytics tools in day-to-day work, or a compelling demonstration of rapid learning and genuine enthusiasm.
• Ability to critically assess AI-generated outputs — spotting errors, challenging assumptions, and knowing when human judgement must override.
• Degree in engineering, mathematics, statistics, computer science, physics, or a related quantitative field — or equivalent demonstrated capability.
• Experience building or contributing to agentic workflows, AI skills, or prompt libraries.
• Retail analytics background including consumer behaviour, promotional analysis, or transaction data.
• Experience mentoring, training, or supporting peers — formal or informal.
• Interest in experimental design, causal inference, or statistical methods beyond standard ML.
• Previous exposure to product development environments or agile ways of working.
• Understanding of data governance, privacy considerations, and ethical AI practices.

Skills

• Data Science
• Artificial Intelligence
• Python
• SQL
• AI Coding Tools
• Analytics Tools
• Claude
• Claude Code
• GitHub Copilot
• Agentic Development
• GCP
• BigQuery
• Data Engineering Tools
• Version Control
• Testing
• Deployment Workflows
• Experimental Design
• Feature Engineering
• Statistical Modelling
• Model Development
• Prompt Engineering
• CI/CD Pipelines
• Docker

Location

• Australia
• India
• UK
• North America

Work Type

• Hybrid
• Flexible work arrangements
• Remote working

Experience Level

• Senior Analyst
• 4–7 years of experience

Education Level

• Degree in engineering, mathematics, statistics, computer science, physics, or a related quantitative field — or equivalent demonstrated capability

Benefits

• Flexible work arrangements
• Global mobility
• Remote working for up to 2 months every year

About the Company

• 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.
• Quantium has 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.
• Quantium is transforming into an AI-native organisation.
• Quantium has 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 analytical workflows.
• The team operates across three domains: Retail Products, AI Client, and AI Enablement.