Senior Analytics - Regulatory Solutions
Nubank
| Company | Nubank |
| Category | Data & Analytics |
| Location | Mexico City |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Senior |
| Salary | Not stated by the employer |
| Posted | 20 Jul 2026 |
| Last verified | 6 Aug 2026 |
| Source | Employer ATS (ashby) |
Description
ABOUT NU
Nu is the leading digital bank in Latin America, serving 135 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
Regulatory Solutions Analytics at Nubank
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.
About the Role
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.
As a Sr Analyst in Regulatory Solutions Analytics, you’re expected to
- 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.
- Under