• Build upon and scale our in-house product analytics solution, enabling self-serve analytics for teams across Product, Engineering, Design, Marketing and Sales • Leverage AI tools (Claude Code, Cursor) as core productivity multipliers in your daily workflow - we expect 10x productivity gains through AI-first approaches • Interpret complex data sets and communicate insights effectively to both technical and non-technical audiences • Translate business requirements into technical requirements for engineers • Manage and evolve our in-house customer data platform, ensuring accurate tracking implementation and maintaining data taxonomy • Analyse user behaviour and product metrics for our analytics, trading and staking products, translating insights into actionable product improvements • Enhance quantitative analyses with qualitative insights derived from user studies and feedback • Build and maintain data models and transformations using dbt

• Partner cross-functionally to support analytics needs for a specific product area or initiative. • Write SQL queries and use analytics tools to create datasets and analyses that measure product usage, performance, and customer outcomes. • Build and maintain dashboards and recurring reports that help teams monitor key metrics and trends. • Support experimentation efforts by helping define success metrics and analyzing results of A/B tests and product experiments. • Develop a strong understanding of product and operational data sources to ensure accurate and consistent reporting. • Enable self-service capabilities and build on trustworthy datasets. • Perform data quality checks and proactively identify anomalies or inconsistencies and improve data processes. • Translate analytical findings into clear insights and recommendations for product teams. • Contribute to shared analytics documentation, metric definitions, and best practices. • Proactively identify areas outside the regular stream of business requests where analytics can add value.

• Uncover critical insights by forming hypotheses and validating them with data. • Identify global and local trends in user behavior to inform product decisions. • Analyze and interpret customer metrics to measure impact and value. • Design and evaluate A/B tests with prospective customers to optimize performance. • Handle ad-hoc analytical requests from stakeholders across the organization.

• Uncover critical insights by forming hypotheses and validating them with data. • Identify global and local trends in user behavior to inform product decisions. • Analyze and interpret customer metrics to measure impact and value. • Design and evaluate A/B tests with prospective customers to optimize performance. • Handle ad-hoc analytical requests from stakeholders across the organization.