Senior Data Analyst

At Figure, we’re redefining what’s possible at the intersection of finance and technology. Fresh off our IPO, we are building the next generation of financial infrastructure, transforming how capital moves, how credit is assessed, and how customers experience financial products. Our data team sits at the heart of that transformation, serving as the analytical engine that powers the entire business. From architecting the data models that drive risk and capital allocation to delivering the reporting and insights that guide growth strategy and operational excellence, we ensure every department has the intelligence needed to win.

As a Senior Data Analyst, you will be a vital driver of our growth and product evolution, partnering closely with Marketing, Product Management, and Engineering to optimize the borrower journey. Your work will directly influence how we acquire customers, the efficiency of our loan application funnel, and the long-term value of our customer base.

You will bridge the gap between user behavior and business strategy, combining analytical rigor with product intuition to help leaders understand the "how" and "why" behind the customer experience. While your primary focus is on the front-end growth engine, you are a generalist at heart—capable of architecting data models that serve the entire organization’s need for clear, actionable intelligence from top-of-funnel to capital allocation.

What You’ll Do

• Data Modeling & Architecture: Design and implement robust data models that transform fragmented marketing spend and application event logs into structured, "gold-standard" datasets. You will ensure our product and acquisition data is clean, organized, and optimized for cross-functional use.

• Funnel Optimization: Build and maintain scalable frameworks to monitor the loan application funnel—identifying friction points, drop-off behaviors, and opportunities to improve conversion from lead to funded loan.

• Technical Impact: Elevate our analytics toolkit by writing high-performance BigQuery SQL and designing intuitive Tableau dashboards that empower stakeholders to track KPIs like CAC (Customer Acquisition Cost), Approval Rates, and Origination Volume in real-time.

• Experimental Design: Partner with Product and Marketing to design, execute, and analyze A/B tests, ensuring we make evidence-based decisions on everything from landing page optimization to credit offer presentation.

• Cross-Functional Insight: Act as the analytical backbone for the business, translating complex user behaviors into repeatable, automated insights that drive measurable growth and product-market fit.

What We Look For

• 3–5+ years of experience using data to drive measurable business impact, specifically within Growth, Product Analytics, or Marketing Science.

• Deep proficiency in SQL (preferably BigQuery); you are an expert at handling complex joins and window functions to reconstruct user journeys across marketing touchpoints and loan applications.

• Advanced Data Modeling: Proven ability to design and maintain structured datasets (star schemas, dbt models) that turn messy clickstream and CRM data into reliable tables for the entire business.

• Expertise with Tableau: You don’t just report data; you build intuitive dashboards that help managers visualize cohort performance, attribution models, and funnel velocity.

• Statistical Depth: Strong grasp of statistical concepts like survival analysis (to model time-to-repayment or time-to-next-loan), causal inference, and significance testing.

• Fintech/Lending Context: Understanding of the lending lifecycle—from initial acquisition through underwriting to funding—and how product changes impact portfolio quality.

• Communication: Clear, confident ability to translate complex data trends into actionable stories for both technical teams and executive leadership.

• Adaptability: A generalist mindset—you are comfortable navigating the ambiguity of a fast-moving environment and can apply your analytical toolkit to solve problems across different business domains.

• Adhere to all company security policies and data handling procedures.

• Complete mandatory security awareness training within required timeframes.

• Promptly report any suspected security incidents or suspicious activity to the Security team.