Lead/Staff Data Scientist

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

Offered From the posting source checked Jun 20, 2026

Learning budget

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Verification

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Salary

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

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

Role

Role function

Data From the posting source checked Jun 20, 2026

Seniority

Senior From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Company

Company stage

Public-company From the posting source checked Jun 20, 2026

Equity

Offered From the posting source checked Jun 20, 2026

Application

Cover letter

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

Lead/Staff Data Scientist Brazil, Belo Horizonte; Brazil, Campinas; Brazil, Rio de Janeiro; Brazil, Sao Paulo About us Nu was born in 2013 with the mission to fight complexity to empower people in their daily lives by reinventing financial services. We are one of the world's largest digital banking platforms, serving millions of customers across Brazil, Mexico, and Colombia. For more information, visit our institutional page https://international.nubank.com.br/careers/ Data Science at Nubank Data Science is essential to every part of the business at Nubank, since Day 1. Most areas of the company use data science to some extent. Data Scientists are responsible for translating business needs into models and other types of data-driven solutions. As a Data Scientist, you're expected to - Interact with other team members to understand how to best apply data science and artificial intelligence to Nubank's problems; - Investigate problems and discover insights through exploratory data analysis and other quantitative methods; - Have great numerical and analytical literacy, including knowledge of statistics and linear algebra as needed; - Work on multiple stages of the ML model lifecycle-from ideation to training and steady-state operation; - Work across multiple types of models, algorithms and learning paradigms; - Communicate technical points, decisions and tradeoffs to peers and stakeholders; Our ideal candidate - Has experience working with ML models in a production environment; - Understands possible pitfalls and tradeoffs when applying ML to real-word, sometimes messy problems; - Is familiar with the technical aspects of learning theory and algorithms and is able

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