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Model Risk Specialist

Nu Holdings Ltd. - Brazil, Sao Paulo

Posted May 13, 2026

Benefits

Parental leave
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Non-birth-parent leave
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Family-building benefits
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  • Surrogacy assistance: Not verified
Mental health support
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Market context

Median wage (BLS OEWS)
$106,409 national median
Projected growth (BLS Employment Projections)
+7.7% - Faster than average

Matched to SOC 13-2011 - Finance aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

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Weekend work
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Application

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Assessment
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Deadline
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Where they hire

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About this role

Model Risk Specialist Brazil, Sao Paulo About Us 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. 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. Visit our institutional page https://international.nubank.com.br/careers/ Our Model Risk team At Nubank we heavily rely on data, machine learning, AI, and other quantitative models & techniques to drive our strategy and provide the best experience and products to our customers. The position holder will be part of the Model Risk team, within the Risk Management structure at Nubank. The Model Risk team is the second line of defense for our models. Our mission is to ensure Nubank relies on world-class solutions that will lead to optimal and sustainable decisions. We act by providing independent review & challenge to models, staying tuned to cutting edge techniques, along with business, customers and regulatory needs. We also work to identify and control risks related to our models, as well as in the definition and implementation of feedback loops to

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