Senior Business Analyst, Credit & Analytics

• Knowledge of Latin American credit data and open finance ecosystems (e.g., Mexico, Brazil, Colombia) • Experience implementing, validating or monitoring risk and scoring models alongside data science teams • Experience supporting collections strategy or early-warning programs • Experience with visualization tools such as Tableau, Metabase, Claude Visualization Tools. •

Jeeves is the stablecoin-native banking platform for global enterprises. Thousands of companies across 35 countries run their corporate cards, payments, treasury and spend on one platform, with more than $5B in annualized volume, payouts to 190 countries, and one of the fastest-growing stablecoin payment networks in the world. BMW, H&M, Lululemon, Burger King, Kavak and XP are among them, and more than 80% of customers use multiple Jeeves products. We chose hard problems on purpose. We hire for one thing: relentlessness. A strong motor that keeps going when the problem has no playbook. You'll know in your first week if Jeeves is right for you. For the right people, it's the steepest learning curve of your career. Jeeves has raised more than $400 million in equity funding from Andreessen Horowitz, Y Combinator, CRV, Coinbase Ventures, GIC, AllianceBernstein, CoinFund and others. If you want to rebuild how money moves across borders, come build it with us. Jeeves extends credit to thousands of businesses across Latin America and beyond, and the quality of those decisions depends on the quality of our data. Our Credit & Analytics team has a clear roadmap: reliable portfolio monitoring, better risk models, and more automated credit decisioning. All of it depends on first getting our data foundation right — connecting and maintaining external data sources and cleaning up customer data consents — and today that work competes with day-to-day execution for the same few people. We're looking for a hands-on Senior Business Analyst to own that foundation and build on it. In your first months you'll lead the work to connect and validate external data (bureau, banking, open finance and tax data), clean up consent records so we can use that data reliably, and turn manual processes into repeatable ones. From there you'll use that data to shape credit policy: underwriting criteria, credit limit strategies, portfolio monitoring and early-warning signals that help us catch losses before they happen. This is a senior individual contributor role for someone who likes to get into the data themselves. You'll partner closely with data science, engineering, product, collections and sales, and your work will directly shape how Jeeves makes credit decisions as we scale. It is not a people-management role today. Location: This is a full-time remote position. What You'll Do: Data Foundation • Lead the integration and validation of external data sources — credit bureaus, bank and open finance data, tax and financial data — partnering with engineering on pipelines and data quality • Own the cleanup of customer data consents and connections so external data can be pulled and refreshed reliably and in line with local requirements • Replace manual credit and portfolio processes with repeatable, documented SQL/Python workflows • Define data quality checks and documentation so the team can trust what it's looking at Credit Policy & Strategy • Use internal performance and external data to develop and refine underwriting criteria and credit limit strategies • Design customer management strategies, including credit line increases, decreases and reinstatements • Identify high-risk customers early and build processes to mitigate losses • Partner with Sales and Business Development so growth strategies stay consistent with Jeeves's credit policy Portfolio Monitoring & Collections Support • Define portfolio KPIs and build dashboards to track portfolio health and strategy performance • Build early-warning signals and monitoring routines that flag deteriorating accounts • Give Collections the segmentation and prioritization insights they need to improve recovery • Contribute to loss forecasting and risk-adjusted return analysis with Finance Models & Automation • Apply statistical methods (logistic regression, segmentation, clustering) to uncover risk drivers and inform strategy • Develop, validate and monitor credit risk models • Help define the rules and data requirements for automated credit decisioning with Product and Engineering • Translate model results into clear recommendations for credit leadership and business partners Working With AI • Use AI tools to support your analysis, and verify their outputs against source data • Suggest and help build improvements to our AI workflows as you see what works and what doesn't Minimum Requirements: • 3–7 years of analytics experience in credit risk, with hands-on work on commercial or SMB credit in cards, payments, lending or a related industry • Advanced SQL — you write your own queries against large, messy datasets and are comfortable validating data quality • Working proficiency in Python for analysis and statistical modeling (regression, segmentation, clustering) • Experience with version control (e.g., GitHub) for sharing and maintaining code is a plus • Able to work independently and take ownership • Direct experience working with external or alternative data sources (bureau, banking, open finance, tax or similar), ideally including integrating or cleaning them • Experience using AI tools such as Claude, ChatGPT or Gemini in your analytical work, and curiosity about using them more • A track record of turning analysis into a credit policy or strategy change that was implemented, with measurable results • Clear written and verbal communication — you can explain a model result or data issue to a non-technical stakeholder • Professional fluency in English — Jeeves is a global company and English is the language we use internally to communicate between regions • Able to work with meaningful overlap with Latin American business hours Preferred Qualifications • Knowledge of Latin American credit data and open finance ecosystems (e.g., Mexico, Brazil, Colombia) • Experience implementing, validating or monitoring risk and scoring models alongside data science teams • Experience supporting collections strategy or early-warning programs •