• Extensive experience and advanced proficiency in SQL and Python/R, capable of writing highly optimized, complex queries and scripts.
• Hands-on experience integrating generative AI (like Claude Code) into your daily analytics workflow for code generation, data formatting, and rapid problem-solving.
• Deep understanding of experimental design, statistical significance, sample size requirements, and the analysis of A/B tests to confidently guide product decisions.
• 5+ years in data analytics or business intelligence, with a strong preference for experience in B2B SaaS.
• Proficiency in using tools like Looker, Tableau, Power BI, or similar to creating compelling, insightful dashboards that drive action.
• Demonstrated ability to handle large datasets, build predictive machine learning models, and perform advanced exploration data analysis.
• Familiarity with tools like Google Analytics, Pendo, or Mixpanel to analyze user flows and feature adoption.
• The ability to distill complex analytical concepts into clear, concise, and persuasive narratives for leadership and cross-functional teams.
• A systematic approach to complex business problems, ensuring analytical efforts are always tied to measurable business value and objectives.
• Proven ability to manage competing priorities, lead analytical projects, and foster a culture of continuous learning by mentoring junior analysts.

• Use data to help the product and marketing teams develop strategic priorities, focusing on core SaaS metrics (e.g., MRR, LTV, CAC, Churn, Retention, and Product-Led Growth signals).
• Lead end-to-end A/B and multivariate testing strategies. Work with the business to define hypotheses, design rigorous experiments, and analyze results to optimize customer journey.
• Utilize AI tools (e.g., Claude Code, Codex, etc.) to accelerate your workflow, whether it’s automating complex SQL queries, generating boilerplate Python/R scripts, or synthesizing large datasets into actionable summaries.
• Use your expert SQL skills to perform complex joins, filter, clean, and transform data from multiple sources to build robust datasets.
• Apply statistical techniques and predictive modeling to understand customer behavior, forecast trends, and derive actionable insights into new feature launches and platform usage.
• Interpret and communicate complex quantitative findings clearly and accurately to non-technical stakeholders, translating data into strategic recommendations.
• Create and maintain automated dashboards to report on core performance metrics and product health.
• Partner with cross-functional teams to establish strategic goals, signals, and metrics to deeply understand and drive overall business performance.

If you're interested in this role, click 'apply now' to forward an up-to-date copy of your CV, or call us now.

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This posting is for an existing vacancy with the organization.

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