Description:
As a result of our incredible success and growth, we are looking for a Senior Product Analyst to join us.
Responsibilities include
- Lead the strategic analytical agenda for the Squad, shaping OKRs, prioritising high-value work, and challenging assumptions to ensure data-driven decision making
- Proactively explore user behaviour and product performance to inform ideation, discovery, and roadmap direction
- Translate complex behaviour and business questions into testable hypotheses and guide experimentation design, execution, and interpretation
- Deliver clear, actionable insights through robust deep-dives, ad-hoc analysis, and ongoing product health reporting
- Ensure data integrity by advising on tracking requirements, maintaining monitoring and alerting, and enabling early detection of behavioural or feature shifts
- Champion a strong data culture by educating Squad members, advocating best-practice analytics, and sharing insights across the organisation
Requirements
A little bit about you.
We'd really like to hear from you, if you have
- Advanced SQL - You must be able to write complex, optimized queries (e.g., using window functions, CTEs, complex joins) to extract and manipulate data from large, complex datasets (e.g., Snowflake, BigQuery, Redshift)
- Data Visualization & BI - Mastery of a modern data visualization tool (e.g., Count.io, Looker, Lightdash, or Metabase). You have a proven track record of building insightful, automated, and user-friendly dashboards for product and business stakeholders
- Product Analytics Platforms & Instrumentation - Familiarity with event-based product analytics tools (e.g., Amplitude, Mixpanel, Heap). A strong understanding of front-end and mobile analytics tracking design and instrumentation is highly desired, particularly with tools like Snowplow
- Experimentation & A/B Testing - Deep knowledge of experimental design. You will partner with Product Managers to advise on proper A/B/n test setup, define key primary and secondary metrics, and conduct the in-depth statistical analysis of results. Must have a strong understanding of statistical significance, confidence intervals, and hypothesis testing
- Product Analytics Frameworks - Expertise in applying analytical frameworks to understand user behavior, including funnel analysis, cohort analysis, user segmentation, and retention/churn analysis
- Data Team Collaboration - Proven experience working alongside Data Engineers and Analytics Engineers. Must understand the differences in their roles and how to partner with them effectively to define data requirements, influence pipeline design, and productionise analyses