Senior Business Analyst, Credit & Analytics

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.

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

Experience with visualization tools such as Tableau, Metabase, Claude Visualization Tools.

Fluency in Spanish and/or Portuguese

Experience in a high-growth startup or fintech