模型风险高级专员
Model Risk Senior Specialist
关于Nu
Nu是拉丁美洲领先的数字银行，为巴西、墨西哥和哥伦比亚的1.4亿客户提供服务。公司通过利用数据和专有技术，开发创新产品和服务，引领行业变革。
秉承着对抗复杂性并赋能人们的使命，Nu为客户提供完整的金融旅程，通过负责任的贷款和透明度促进金融准入和发展。公司由一个高效且可扩展的商业模式驱动，结合低成本的服务与不断增长的回报。
Nu的影响已获得多项奖项的认可，包括《时代》100家最具影响力公司、《快公司》最具创新力公司以及《福布斯》全球最佳银行。
访问我们的机构页面 https://www.nu.com/2026-en
关于团队
在Nubank，我们高度依赖数据、机器学习和其他定量模型与技术来推动我们的策略，为客户提供最佳体验和产品。
职位持有人将加入Nubank风险管理部门中的模型风险团队。
模型风险团队是我们模型的第二道防线。我们的使命是确保Nubank依靠世界级的解决方案，实现最优、可持续的决策。我们通过提供独立的审查与挑战，关注前沿技术，并与业务、客户和监管需求保持一致来发挥作用。我们还致力于识别和控制与模型相关的风险，并定义和实施反馈机制以持续改进模型。
你将负责
- 基于统计和机器学习技术对定量模型进行独立审查，识别并验证模型的用途、假设、数据、方法论以及符合监管要求的情况。
- 提供有效的挑战，识别风险和改进机会，与相关方合作以强化我们的决策工具。
- 提出并监控KPI，解释模型表现如何影响Nubank的业务。
- 与不同相关方（包括高级管理人员和监管机构）讨论并报告模型风险状况和独立意见。
- 跟进模型在业务中的应用和使用情况，理解其对决策的实际影响，并为反馈机制做出贡献。
- 开发操作手册和工具包（Python、Scala、AI代理等），以优化模型审查工作
查看英文原文
ABOUT NU
Nu is the leading digital bank in Latin America, serving 140 million customers across Brazil, Mexico, and Colombia. The company has been leading an industry transformation by leveraging data and proprietary technology to develop innovative products and services.
Guided by its mission to fight complexity and empower people, Nu caters to customers’ complete financial journey, promoting financial access and advancement with responsible lending and transparency. The company is powered by an efficient and scalable business model that combines low cost to serve with growing returns.
Nu’s impact has been recognized in multiple awards, including Time 100 Most Influential Companies, Fast Company’s Most Innovative Companies, and Forbes World’s Best Banks.
Visit our Institutional Page https://www.nu.com/2026-en
About The Team
At Nubank, we rely heavily on data, machine learning, and other quantitative models & techniques to drive our strategy and deliver the best experience and products to our customers.
The position holder will be part of the Model Risk team within Nubank's Risk Management structure.
The Model Risk team is the second line of defense for our models. Our mission is to ensure that Nubank relies on world-class solutions that enable optimal, sustainable decision-making. We act by providing independent review & challenge of models, staying tuned to cutting-edge techniques, and aligning with business, customer, and regulatory needs. We also work to identify and control risks related to our models, as well as to define and implement feedback loops to continuously improve them.
You'll be responsible for
- Conduct independent reviews of quantitative models based on statistical and machine learning techniques, identifying and validating models' uses, hypotheses, data, methodologies and compliance with regulatory requirements.
- Provide effective challenges, identify risks and enhancement opportunities, engaging with stakeholders to strengthen our decision-making tools.
- Propose and monitor KPIs to explain how model performance impacts Nubank's business.
- Discuss and report model risk status and independent opinions with different stakeholders, including senior managers and regulators.
- Follow up on how models are applied and used in the business, understanding their practical impact on decisions and contributing to feedback loops.
- Develop playbooks and toolkits (Python, Scala, AI Agents, etc.) to optimize model reviews, ongoing model monitoring, and assess the impact of models on decisions.
- Be exposed to different types of decisions and processes (e.g. credit, fraud, operations) and different countries.
- Contribute to keeping Nubank's model risk governance and standards continuously updated, incorporating new techniques and new model applications as they emerge.
- Work in a multicultural, diverse and highly skilled environment.
We are looking for a person who has
- Experience with development and/or validation of quantitative and/or machine learning models, specifically applied to the credit cycle, fraud prevention or related decision-making processes.
- Data Science skills, with knowledge of machine learning tools and techniques.
- Strong programming skills.
- Proactive, autonomous and able to learn fast, with strong analytical and problem-solving skills, motivated by challenges.
- Organized and detail-oriented, without losing track of the big picture.
- Excellent communication and interpersonal skills, able to discuss complex topics with both technical and non-technical stakeholders.
- English language proficiency.
- Challenge business models to find enhancement opportunities
Preferred Qualifications
- Analytical, problem-solving, and passionate about manipulating data in order to learn from it
- Academic or professional experience in statistical and mathematical model application and/or validation, and/or experience in credit risk management and/or other risk management frameworks.
- Bachelor’s degree in Engineering, Economics, Math, Statistics, Physics or related fields
- Great coding skills (SQL, Python, Scala, Databricks, Github, Cursor or other similar programming languages)
- Desirable knowledge of model risk regulation, such as SR 11-7 (FED) and PRA SS1/23.
- Master's degree or relevant undergraduate scientific project.
Location for this opportunity (City, Country)
- São Paulo, Brazil
Work Model for this Role
- Option 1: Hybrid 2-3 times/week: Our hybrid work model brings us to the office at least twice a week, on strategic days designed to maximize team connection and collaboration. For more details, visit https://building.nubank.com/nu-hybrid-work-model/
OUR BENEFITS
- Chance of earning equity at Nubank;
- Food/ Meal Card (Vale-Refeição and/or Vale Alimentação)
- Public Transportation Commuting Benefit (Vale-Transporte)
- NuCare – Psychological, Financial and Legal Assistance Program
- Life Insurance
- Medical Plan
- Dental Plan
- NuLanguage – Language Course Program
- Nucleo - Our learning platform of courses
- Extended Parental Leave
- Daycare Allowance
- Parental Consultancy
- Work-from-home Allowance
- Gym Partnerships
- 30 days of paid vacation
- Relocation Assistance Package, if applicable
Our recruitment process may involve the use of artificial intelligence–enabled tools, such as automated interview transcription and analysis, to support the evaluation process. Artificial intelligence is not used to make final hiring decisions; all decisions are made by human reviewers.