模型风险专员
Model Risk Specialist
关于Nu
Nu是拉丁美洲领先的数字银行，服务于巴西、墨西哥和哥伦比亚的1.4亿客户。该公司通过利用数据和专有技术推动行业变革，开发创新的产品和服务。
秉承其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进步。公司由高效且可扩展的商业模式驱动，结合低成本服务与持续增长的回报。
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
关于职位
在Nubank，我们高度依赖数据、机器学习，并越来越多地依赖生成式和代理式AI来推动我们的战略，为客户带来最佳体验和产品。模型风险团队在确保与我们的模型和AI系统相关的风险被理解和控制方面发挥着关键作用。我们现在正在建立一个专门的AI风险管理能力，以应对先进AI带来的新兴风险——包括由大语言模型驱动和自主代理系统，重点关注AI质量、模型和代理行为，以及保持这些系统在内部和面向客户用例中安全可靠的平台控制措施。
这是一个个人贡献者角色，你将既审查和评估一线团队所构建的内容，又积极开发工具、指南和分析，以成熟我们的风险实践。你将专注于围绕模型开发和部署的基础设施和数据风险：特征工程和特征存储库、MLOps流水线、模型监控、部署平台和数据治理实践。你将与模型和数据平台团队紧密合作，独立识别、评估和报告风险，提供第二线视角的同时不失去技术深度。
职责
基础设施与数据风险评估
- 对用于开发、部署和监控AI/机器学习模型的数据和基础设施环境进行独立审查，评估其可靠性、稳定性和适用性。
- 评估模型生命周期基础设施中的风险：特征工程流水线、特征存储库、模型的CI/CD、部署平台
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 ROLE
At Nubank we heavily rely on Data, Machine Learning, and increasingly on Generative and Agentic AI to drive our strategy and deliver the best experience and products to our customers. The Model Risk team plays a crucial role in ensuring the risks associated with our models and AI systems are understood and under control. We are now building a dedicated AI Risk Management capability to address the emerging risks of advanced AI — including LLM-powered and autonomous agentic systems — with a focus on AI quality, model and agent behavior, and the platform controls that keep these systems safe and reliable across internal and customer-facing use cases.
This is an individual contributor role, you will both review and assess what first-line teams build, and actively develop tools, playbooks, and analyses to mature our risk practices. You will focus on the infrastructure and data risks that surround model development and deployment: feature engineering and feature stores, MLOps pipelines, model monitoring, deployment platforms, and data governance practices. You will work closely with model and data platform teams to identify, assess, and report risks independently, bringing a second-line perspective without losing technical depth.
RESPONSIBILITIES
Infrastructure & Data Risk Assessment
- Conduct independent reviews of the data and infrastructure environments used for developing, deploying, and monitoring AI/machine learning models, assessing reliability, stability, and fitness for purpose.
- Evaluate risks across the model lifecycle infrastructure: feature engineering pipelines, feature stores, CI/CD for models, deployment platforms, and model monitoring systems.
- Assess data governance practices, including data quality, lineage, access controls and identify gaps that could materially impact model behavior or risk.
- Identify and escalate risks or control gaps proactively across all stages of the model and data platform lifecycle.
Controls & Governance
- Help establish and enhance specific controls and validation practices for data and infrastructure used in model development and deployment.
- Review and challenge first-line processes, procedures, and controls against internal policies, industry frameworks, and regulatory expectations.
- Partner with model and data platform teams to define and monitor Key Risk Indicators (KRIs) for infrastructure and data risk.
- Contribute to the evolution of Nubank's model governance framework with an infrastructure and data lens.
Tooling & Playbooks
- Develop and improve tools, analyses, and playbooks specific to infrastructure and data risk management.
- Build reporting and monitoring solutions that provide clear, continuous visibility into the health of model infrastructure and data environments.
- Support internal audit and regulatory inquiries with well-documented, traceable, and reproducible risk assessments.
Stakeholder Engagement
- Discuss and report infrastructure and data risk status, findings, and independent opinions with stakeholders across the organization, including senior managers.
- Collaborate with model teams, data platform engineers, and governance partners to drive risk-aware design decisions without slowing responsible innovation.
- Work in a multicultural, diverse, and highly skilled environment.
QUALIFICATIONS
- Bachelor's or master's degree in computer science, data science, statistics, mathematics, engineering, or a related field.
- Strong programming skills: Proficiency in Python and SQL; experience with Spark/Scala is a plus.
- ML infrastructure knowledge: Hands-on familiarity with MLOps practices, CI/CD pipelines for models, feature stores, and cloud-based ML platforms (AWS, GCP, or Azure).
- Data governance: Understanding of Data Mesh architecture and principles, data lineage, data quality frameworks, and feature governance practices.
- Model monitoring: Experience with model and data monitoring concepts, including drift detection, pipeline stability, and performance degradation tracking.
- Good written and verbal communication skills in English
- Understanding of risk management principles, control design, and governance frameworks (e.g. ERM, COSO); experience in a 2nd or 3rd line of defense is a strong plus.
- Prior experience in model risk management, model validation, or a data/ML engineering role transitioning into risk (nice to have)
- Familiarity with model risk frameworks and regulatory expectations (e.g., SR 11-7 / SR 26-2 / OCC 2011-12, NIST AI RMF)-(nice to have)
Location & Work Model
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.
This position is based in Sao Paulo, Brazil.
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.