• Partner with cross-functional teams and be the Credit POC that manages the end-to-end credit strategy for the Amazon portfolio • Leverage alternative data and optimize our credit strategy to expand credit reach to the low FICO and credit invisible users • Partner with Machine Learning team to enhance our underwriting framework for high AOV • Support new product formation and new vertical exploration

• Collect, clean, and analyze large datasets to uncover trends, patterns, and actionable insights. • Perform exploratory data analysis to uncover trends, patterns, and anomalies that impact platform trust and safety. • Collaborate with Safety Ops, product, and engineering teams to support investigations of flagged content or behavior. • Support continuous process improvements in data collection, analysis, and reporting workflows. • Help with policy enforcement operations; partner on audits and enforcement efficiency related projects.

• Data Visualization and Reporting: Design, build, and maintain dashboards and reports using Power BI and other approved business intelligence tools. • Translate complex business requirements into user-friendly, visually compelling reporting solutions. • Ensure all visualizations follow enterprise design standards, maintain brand consistency, and meet accessibility best practices. • Continuously enhance existing dashboards based on user feedback and evolving business needs. • Data Analysis & Query Development: Write, refine, and optimize SQL queries to support data extraction, transformation, and analysis across multiple data sources. • Conduct exploratory and descriptive analysis to identify trends, outliers, and opportunities for operational improvement. • Validate the accuracy and consistency of data outputs through quality assurance checks and testing protocols. • Stakeholder Collaboration: Partner with cross-functional teams (including but not limited to finance, operations, clinical, marketing) to understand reporting needs and business goals. • Facilitate conversations with both technical and non-technical stakeholders to ensure alignment of data definitions and report outputs. • Act as a liaison between the business and technical resources, helping to translate business questions into actionable analytics solutions. • Support change management efforts related to new reports, dashboards, or metrics. • Data Governance & Documentation: Support enterprise data governance efforts by helping to define and standardize key metrics and performance indicators. • Maintain clear, up-to-date documentation for all dashboards, data sources, and business logic used in reporting. • Participate in efforts to improve data accuracy, completeness, and integrity across systems. • Assist in auditing and resolving data quality issues in collaboration with data engineering or source system teams. • Analytics Request Management: Assist with the intake, triage, and tracking of analytics and reporting requests, ensuring clarity and prioritization. • Manage the delivery of recurring and ad hoc reports in a timely and accurate manner. • Maintain transparency with stakeholders by communicating timelines, dependencies, and progress updates.

• Translate data into strategy by analysing transactional data and financial performance to generate insights that drive Xapo’s growth. • Synthesise findings and communicate them in a clear, practical, and actionable way through visualisations and storytelling. • Write and manage end-to-end data pipelines. • Design and maintain Looker dashboards to enable self-service analytics for stakeholders. • Act as a strategic partner to the Finance and Treasury teams, as well as other teams across the company, translating business questions into technical data requirements. • Support stakeholders in interpreting and using data in their day-to-day work, providing actionable recommendations based on analysis. • Support the Finance and Treasury teams in identifying and achieving financial efficiencies and delivering strategic recommendations to the business. • Ensure data accuracy and maintain a single source of truth across all reporting. • Automate and improve data processes by implementing analytics and predictive modelling tools. • Continuously identify opportunities to improve data-related processes and approaches.