Senior Analytics - Regulatory Solutions

Nu is one of the largest digital financial platforms in the world, with more than 122 million customers across Brazil, Mexico, and Colombia. Guided by our mission to fight complexity and empower people, we are redefining financial services in Latin America — and this is still just the beginning of the purple future we’re building together.

Listed on the New York Stock Exchange (NYSE: NU), we combine proprietary technology, data intelligence, and an efficient operating model to deliver financial products that are simple, accessible, and human. Our impact has been recognized by global rankings such as Time 100 Companies, Fast Company’s Most Innovative Companies, and Forbes World’s Best Bank.

As a company at the forefront of the financial revolution in Latin America, Nubank has grown exponentially since its inception — and keeping that growth healthy and people-centered depends on making critical, data-informed decisions every day. Regulatory Solutions Analytics is at the heart of that process: our analysts work across teams to structure and analyze data, challenge assumptions, and translate findings into real improvements for our customers.

As a Sr Analyst in Regulatory Solutions Analytics, you bring the depth, autonomy, and technical fluency to lead that work on the most demanding problems — and to raise the bar for the analysts around you. We’re looking for people who are curious, proactive, and energized by solving complex problems: not necessarily those with all the answers, but those who know how to find them.

This role sits in Pack Analytics within Regulatory Solutions (Ops Defense). You’ll turn the analytical demands of our regulatory processes — KYC, AML, Judicial Orders, and others — into advanced analytics, models, and AI-powered solutions, while keeping the highest standard of quality for customer data and due diligence, in line with regulators and internal policies.

You will operate with growing autonomy: you solve well-defined problems independently and take on harder, more ambiguous challenges with the support of your team and manager, beginning to build deep expertise in your domain. Above all, you are excellent with data and genuinely passionate about artificial intelligence, proactively keeping yourself at the frontier of what these tools can do.

• Lead investigative, data-first work end to end: decide which data makes the most sense in each situation and, when it isn’t there yet, design the right tests or approaches to generate it.
• Own advanced data analysis — run root-cause analysis, formulate and test hypotheses, and deliver effective solutions to challenging (though typically well-defined) problems with limited supervision.
• Apply data science and statistical methods (e.g., anomaly detection, classification, segmentation, forecasting) to strengthen, scale, and automate regulatory decisions.
• Use artificial intelligence as a core tool: leverage GenAI/LLMs and modern AI tooling to accelerate analysis, prototype solutions, and automate manual work — and proactively stay at the frontier of AI, bringing new techniques back to the team.
• Work with large volumes of data using SQL, Python, and Scala — writing optimized queries and code to build a solid foundation for decision-making, knowing that not all answers live in the data, and that’s okay.
• Build dashboards and visualizations (e.g., QuickSight, BigQuery) that go beyond the descriptive, surfacing trends, deviations, and forward-looking signals across historical and future horizons.
• Apply solid, practical knowledge of data architecture and modeling (Data Mart, Data Lake, Data Warehouse) for analytical purposes, and manage dataset dependencies.
• Understand our products and how they interact with other areas of the business, translating business, legal, and customer needs into quantitative metrics (KPIs, OKRs).
• Support data-based decisions across your team, making calculated risk-taking comfortable despite uncertainty while keeping project flow.
• Apply data governance fundamentals — data classification, secure access to PII, lineage, quality monitoring, and cost optimization.
• Learn continuously and share knowledge generously, beginning to act as a reference in your area.

• Strong analytical capacity: comfort with numbers and calculations, and the ability to solve problems methodically.
• Excellent with data — advanced data analysis and/or data science — with the appetite to go deep on large, ambiguous transactional datasets.
• Hands-on fluency with SQL and at least one general-purpose language (Python and/or Scala).
• A real passion for artificial intelligence and machine learning, with a proactive habit of keeping up to date and applying new tools to real problems.
• Business basics: understanding the dynamics between risks and opportunities, and how business and technical areas (product/engineering) interact.
• Problem solving: creativity and practicality in tackling day-to-day challenges, with awareness of how your work impacts our customers’ experience and aligns with our purpose.
• Proactive, autonomous, and curious — comfortable solving well-defined problems on your own and escalating the harder, ambiguous ones at the right time.
• Clear, succinct, and effective communication in English and Spanish.
• Openness to feedback and adaptability to a multifunctional, fast-changing environment.

• Have data engineering experience — building and maintaining data pipelines, working with massive parallel processing (e.g., Spark / MPP), and using lineage and orchestration tools. (Data engineering is a strong plus.)
• Hold a degree in a quantitative field (e.g., Computer Science, Engineering, Statistics, Mathematics, Finance, or Physics) with a solid statistical modeling and analysis background.
• Have hands-on experience taking machine learning or AI / GenAI solutions to production.
• Are familiar with “Know Your Customer” and AML / regulatory topics, applicable not only for Mexico but also for Brazil and other Latin American countries.

Mexico City, Mexico

This role is based full-time, on-site, at our Mexico City office.

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