Data Analyst II

• Design and deliver end-to-end analytics solutions from concept through to implementation.
• Prepare, cleanse, validate, and analyse large and complex datasets.
• Translate business requirements into actionable insights and recommendations.
• Build scalable reports, dashboards, and visualisations for key stakeholders.
• Apply statistical techniques and experimentation methodologies, including A/B testing.
• Collaborate with cross-functional teams to identify opportunities and solve business challenges.
• Develop reproducible analytical workflows and datasets.
• Ensure accuracy and quality through validation and peer review processes.
• Present findings clearly to both technical and non-technical audiences.
• Support and mentor junior analysts, sharing knowledge and best practices.
• Utilise emerging AI tools and technologies to improve analytical efficiency., Team Environment You’ll work within a collaborative analytics function alongside:
• Product Managers
• Data Analysts
• Data Engineers
• Software Engineers
• Product Designers
• Business Stakeholders

• Minimum 5 years’ experience in Data Analytics (or 3+ years with a relevant PhD).
• Advanced SQL skills.
• Strong Python and/or PySpark experience.
• Experience working with Snowflake.
• Proven experience across the full data lifecycle, including:
• Data collection
• Data cleansing
• Data modelling
• Data aggregation
• Data validation
• Reporting
• Experience working within technology-focused environments.
• Strong understanding of experimentation methodologies, including A/B testing and randomisation.
• Experience with data visualisation tools such as Tableau, Power BI, or similar.
• Excellent stakeholder management and communication skills.
• Strong analytical and problem-solving capability.
• Experience working within cross-functional product teams.

Desirable

• Experience with causal inference techniques.
• Exposure to behavioural tracking and customer analytics.
• Experience using AI tools such as Claude, Cursor, Cortex, Windsurf, or similar.
• Experience developing AI agents or automation solutions.
• Exposure to Machine Learning or Data Science environments.