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Jeeves is a financial operating system serving 5,000+ clients across 20+ countries, offering corporate cards, cross-border payments, and spend management software. The company has raised $380M+ from top-tier investors including Andreessen Horowitz, Y Combinator, and founders of unicorns like Nubank and Rappi.
You will own the data foundation for Jeeves's Credit & Analytics team, a critical function as the company extends credit to thousands of businesses across Latin America and beyond. This is a hands-on senior individual contributor role (not people management) where you'll partner closely with data science, engineering, product, collections, and sales teams.
In your first months, you'll lead integration and validation of external data sources (credit bureaus, banking, open finance, tax data), clean up customer data consents to enable reliable data usage, and replace manual processes with repeatable SQL/Python workflows. You'll define data quality checks and documentation so the team can trust its data.
You'll then use that foundation to shape credit policy: developing and refining underwriting criteria, designing customer management strategies (credit line increases/decreases/reinstatements), identifying high-risk customers early, and building processes to mitigate losses. You'll define portfolio KPIs, build dashboards to track portfolio health, create early-warning signals for deteriorating accounts, and provide Collections with segmentation and prioritization insights.
Your analytical work will include applying statistical methods (logistic regression, segmentation, clustering) to uncover risk drivers, developing and validating credit risk models, and helping define rules for automated credit decisioning. You'll translate model results into clear recommendations for credit leadership and business partners. You'll also use AI tools to support analysis, verify their outputs, and suggest improvements to AI workflows.
This role offers direct impact: your work will shape how Jeeves makes credit decisions as the company scales across Latin America and beyond.
Requirements:
- 3–7 years of analytics experience in credit risk, with hands-on work on commercial or SMB credit in cards, payments, lending, or related industry
- Advanced SQL: write your own queries against large, messy datasets and validate data quality
- Working proficiency in Python for analysis and statistical modeling (regression, segmentation, clustering)
- Direct experience with external or alternative data sources (bureau, banking, open finance, tax, or similar), ideally including integration or cleaning
- Experience using AI tools (Claude, ChatGPT, Gemini) in analytical work, with curiosity to use them more
- Track record of turning analysis into implemented credit policy or strategy change with measurable results
- Clear written and verbal communication; ability to explain model results or data issues to non-technical stakeholders
- Professional fluency in English (required for internal global communication)
- Ability to work with meaningful overlap with Latin American business hours
- Version control experience (e.g., GitHub) is a plus
- Ability to work independently and take ownership
Preferred: Knowledge of Latin American credit data and open finance ecosystems (Mexico, Brazil, Colombia); experience implementing/validating/monitoring risk and scoring models with data science teams; experience supporting collections strategy or early-warning programs; visualization tools (Tableau, Metabase); fluency in Spanish and/or Portuguese; high-growth startup or fintech experience.
