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Jeeves is a groundbreaking financial operating system built for global businesses that provides corporate cards, cross-border payments, and spend management software within one unified platform. The company operates across 20+ countries including Brazil, Canada, Colombia, Mexico, the United Kingdom, across Europe, and the United States, and serves over 5,000 clients ranging from venture‑backed startups to SMBs around the world. With a mission to empower businesses with more efficient and cost‑effective financial solutions worldwide, Jeeves combines cutting‑edge financial technology with exceptional team expertise to transform the business financial landscape. Jeeves has been recognized as one of The Information's 50 Most Promising Startups in 2023, as well as a Y Combinator Top Company 2021-2023 and won “Fintech of the Year” at the European Fintech Awards.

Since graduating from Y Combinator in 2020, Jeeves has successfully raised over $380 million and is backed by top world‑class investors including Andreessen Horowitz, Y Combinator, CRV, Tencent, Stanford University, Clocktower Ventures, and founders of more than 15 unicorns including David Velez (Nubank), Carlos Garcia (Kavak) and Sebastián Mejía (Rappi).

We are seeking a highly analytical Credit Analyst to help develop data‑driven credit policies and support the growth of Jeeves’ global credit portfolio. In this role, you will use a wide range of internal and external data sources to refine underwriting criteria, strengthen new customer originations, and reduce credit risk. You will contribute to advancing our data and analytics framework, leveraging statistical methods and credit risk models to generate insights and drive strategy. Additionally, you will enhance credit monitoring and governance by building dashboards, improving reporting processes, and refining risk rating practices. This role requires strong technical proficiency, a solid foundation in credit risk analytics, and the ability to turn complex data into actionable business strategies.

Location: This role is based out of São Paulo, Brazil, and is a full‑time position where it is required to come into our office at complexo JK Iguatemi (2-3 days/week). #LI‑Hybrid

• Develop best in class data‑driven credit policies and business strategies: Leverage external (e.g. banking, tax, financial, credit bureau and other data) and internal performance data to develop credit policies (e.g. underwriting criteria, dynamic credit limit programs, etc.). Minimize credit loss by developing and implementing appropriate processes and procedures to identify and mitigate high risk customers. Design and implement data‑driven strategies to improve funnel metrics and credit quality for new customer originations. Work closely with the sales and business development teams to support business growth strategies that preserve effective underwriting and ensure the appropriate application of Jeeves’ credit policy.
• Deliver advancements in data and analytics: Contribute to the development of a data and analytics framework to improve processing, underwriting, tracking, risk management, and reporting procedures. Design and execute data driven analyses and tracking procedures to enhance insights on credit risk for individual, and the portfolio of companies. Leverage predictive statistical methodologies (e.g., linear/logistic regression, segmentation analysis) to draw insights and develop business strategies. Partner with data scientists to build and leverage credit risk models to optimize credit policies and improve business performance.
• Improve credit monitoring and governance: Build dashboards to monitor portfolio health and strategy performance. Develop and implement improvements to credit portfolio monitoring, client review tracking, management reporting, and customer risk rating assignments.

• 4+ years in analytics within credit risk management.
• Fluent in English, Jeeves is a global company and English is the language we use internally to communicate between regions.
• Excellent written and verbal communication skills.
• Intellectual curiosity.
• Ability to translate complex data and model results into actionable business strategies.
• Proficiency in SQL and Excel.
• Experience using Python or R for data analysis and statistical modeling (regression, clustering, etc.).

• Experience in commercial credit risk, specifically within credit cards, payments, lending, or related industries.
• Experience utilizing alternative data sources.
• Experience in architecting, implementing, and interpreting risk/scoring models in conjunction with data science teams.
• Experience in high growth startups preferred.
• Experience with visualization tools such as Tableau.
• Experience building complex financial products and models.