Lead/Staff Data Scientist

Benefits

Parental leave

Not verified

Non-birth-parent leave

Not verified

Family-building benefits

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

Mental health support

Not verified

Relocation assistance

Not verified

Childcare support

Not verified

Learning budget

Not verified

Verification

Not verified

Salary

Not verified

Was this benefit information wrong? Tell us.

Schedule

Shift type

Not verified

Weekend work

Not verified

Application

Cover letter

Not verified

Assessment

Not verified

Deadline

Not stated

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

Read the full description at job-boards.greenhouse.io. FewerJobs shows a source-linked preview and links to the original posting.