Principal Data Analyst, Figure

• 7+ years of experience using data to drive measurable business impact
• Deep proficiency in SQL (preferably BigQuery) and expertise with complex joins, subqueries, and recursive logic
• Advanced experience with Tableau; you know how to build dashboards that influence decisions, not just report them
• Strong understanding of risk modeling, credit analytics, or capital markets data structures
• Proven experience in fintech or financial services environments
• Working knowledge of Python for data manipulation, automation, or modeling
• Appreciation for statistical concepts like causal inference, bias detection, and experimental design
• Clear, confident communication with both technical and non-technical audiences
• Comfort navigating ambiguity and setting analytical direction in fast-moving environments
• A natural curiosity about how finance, technology, and data intersect to drive innovation

Desirable

• As a Principal Data Analyst, you will be a cornerstone of our analytics organization, partnering closely with Credit/Risk and Capital Markets to drive real financial outcomes
• Your work will directly influence lending decisions, portfolio optimization, and the strategies behind our capital markets platform
• You will connect analysis to the bigger picture across markets, products, and mission, combining analytical rigor with business intuition to help leaders understand what is happening and why it matters
• You will also elevate our toolkit by building intuitive Tableau dashboards, writing performant BigQuery SQL, and designing frameworks that make insights repeatable and scalable across the company
• Act as the analytics lead for Credit/Risk and Capital Markets, guiding decision-making through data-driven insights
• Partner with cross-functional leaders to shape the questions that matter most, then answer them through thoughtful analysis and storytelling
• Design and maintain robust Tableau dashboards that translate data into actionable narratives
• Write and optimize BigQuery SQL to extract, transform, and analyze large-scale datasets
• Develop analytical frameworks and models that support risk forecasting, pricing strategies, and portfolio performance
• Apply statistical and experimental methods to test hypotheses, quantify uncertainty, and inform strategic trade-offs
• Communicate findings clearly and persuasively to senior stakeholders
• Champion a culture of data accuracy, curiosity, and continuous improvement