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/  

About the team

Portfolio Solutions is the team within Nu Asset Management responsible for the firm's ETFs and systematic fundos, and the allocation models behind our products and the broader Nubank ecosystem. We believe most of an investor's long-term return comes down to three things: cost, allocation, and discipline. Our job is to deliver all three at scale — which means we treat infrastructure, automation, and AI tooling as core to investment research, not as side projects.

We're looking for a quantitative analyst to strengthen our research, index construction, allocation modeling, and the platform that ties it all together.

What you'll do

• Research, design, and implement indices and systematic strategies across fixed income, equities, and derivatives — including structures such as covered calls, duration barbells, and factor portfolios
• Build and maintain multi-asset allocation models, with attention to efficient replication, tracking error control, and transaction costs
• Run rigorous backtests: no look-ahead, no survivorship, realistic costs. We don't publish a curve without out-of-sample replication
• Help build the quantitative infrastructure of the team: reusable data pipelines, backtest frameworks, monitoring dashboards, and reporting workflows on Databricks. The goal is that every model you build outlives the project it was born in
• Develop AI-powered tools for investment research: LLM-driven analysts on top of our internal datasets, agents for routine analytical tasks, copilots that compress the distance between question and answer for the whole team
• Support the launch of new ETFs — from index methodology to interactions with index prodviders, market makers, administrators, and custodians
• Read papers, replicate results, and tell apart what works from what looks like it works

What we're looking for

• Bachelor's degree in a quantitative field: engineering, math, physics, statistics, economics, computer science, quantitative finance, or equivalent
• 3+ years in quantitative research, systematic asset management, risk, or adjacent roles 
• Strong Python (pandas, numpy, scipy). Comfort writing code that other people will read, run, and extend
• Curiosity about — and ideally experience with — building production-grade analytical infrastructure: pipelines, jobs, dashboards, internal tools
• Genuine interest in applying LLMs and AI agents to quantitative work, not just as users but as builders
• Familiarity with the Brazilian market: NTN-B, IMA, Ibovespa, B3 derivatives, local ETF dynamics
• A collaborative, constructive way of working: you ask for help when stuck, you offer help when others are, you document, you review code, you disagree clearly without making it personal, and you give credit generously
• Ability to communicate quantitative results clearly — to portfolio managers, commercial teams, and ultimately to the end investor

Nice to have

• CFA, CAIA, FRM, or a graduate degree in a quantitative field
• Experience with ETFs, index replication, or benchmark construction
• Hands-on Databricks (Workflows, Delta, Unity Catalog, Databricks Apps), version control discipline, MLOps fundamentals
• Experience designing or shipping internal tools, copilots, or RAG systems

Benefits

• Chance of earning equity at Nubank
• Food/ Meal Card (Vale-Refeição and/or Vale Alimentação)
• Public Transportation Commuting Benefit (Vale-Transporte)
• NuCare – Psychological, Financial and Legal Assistance Program
• Life Insurance
• Medical Plan
• Dental Plan
• NuLanguage – Language Course Program
• Nucleo - Our learning platform of courses
• Extended Parental Leave
• Daycare Allowance
• Parental Consultancy
• Work-from-home Allowance
• Gym Partnerships
• 30 days of paid vacation
• Relocation Assistance Package, if applicable

Hybrid 2-3 times/week: Our hybrid work model brings us to the office at least twice a week, on strategic days designed to maximize team connection and collaboration. For more details, visit https://building.nubank.com/nu-hybrid-work-model/

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 to discuss details if needed;
• Has experience working with the Python scientific stack (Numpy, Pandas, Scipy, Sklearn, Boosted Tree Libraries, etc);
• Has experience working with Tensor/Deep Learning libraries such as Tensorflow and Pytorch;
• Is able to connect analytical outcomes to business priorities and advise stakeholders on the best course of action;
• Has good communication skills and is able to convey technical topics and decision points to diverse audiences;
• Has experience writing general-purpose code using modern tools;
• Understands the implications of causality when applying ML to problems;
• Is up-to-date with recent developments in the area as a whole and is able to identify opportunities for improvement and innovation;
  
  

Our Benefits

• Chance of earning equity at Nubank
• Food/ Meal Card (Vale-Refeição and/or Vale Alimentação)
• Public Transportation Commuting Benefit (Vale-Transporte)
• NuCare – Psychological, Financial and Legal Assistance Program
• Life Insurance
• Medical Plan
• Dental Plan
• NuLanguage – Language Course Program
• Nucleo - Our learning platform of courses
• Extended Parental Leave
• Daycare Allowance
• Parental Consultancy
• Work-from-home Allowance
• Gym Partnerships
• 30 days of paid vacation
  
  

Work Model for this Role

Hybrid 2-3 times/week: Our hybrid work model brings us to the office at least twice a week, on strategic days designed to maximize team connection and collaboration. For more details, visit https://building.nubank.com/nu-hybrid-work-model/

A Capco é uma consultoria global de tecnologia e negócios, focada no setor de serviços financeiros e energia, somos apaixonados por ajudar nossos clientes, temos 40 escritórios nas Américas, Europa e Ásia-Pacífico! Se criatividade e inovação são sua paixão, a Capco é ideal para você. Vamos te apoiar e ajudar a acelerar sua carreira!

Estamos em busca de um(a) Machine Learning Engineer com foco em NLP e processamento de documentos para atuar no desenvolvimento de soluções inteligentes voltadas à automação e análise de dados, especialmente em contextos financeiros. O(a) profissional será responsável por construir pipelines de dados, desenvolver modelos de machine learning e implementar soluções escaláveis em ambiente cloud.

O que você fará:

• Desenvolver soluções de machine learning e NLP para extração e processamento de informações de documentos
• Trabalhar com OCR, parsing de PDFs e extração de dados de Excel
• Implementar algoritmos de fuzzy matching (ex: Levenshtein, record linkage)
• Construir e manter pipelines de dados e processos de ETL
• Desenvolver, treinar e validar modelos de machine learning (supervisionados e não supervisionados)
• Realizar deploy de modelos utilizando APIs REST, Docker e serviços Azure
• Integrar soluções com sistemas externos e aplicações corporativas
• Colaborar com times multidisciplinares para entrega de soluções escaláveis

O que você precisa ter:

• Forte experiência em Python (Pandas, NumPy, scikit-learn)
• Experiência com bibliotecas de NLP (spaCy, NLTK ou Transformers)
• Conhecimento em processamento de documentos (OCR, PDFs, Excel)
• Experiência com deploy de modelos (APIs REST, Docker, Azure ML)
• Entendimento de técnicas de machine learning supervisionado e não supervisionado
• Experiência com pipelines de dados e ETL
• 2 a 5 anos de experiência em Machine Learning, com foco em NLP ou dados financeiros
• Inglês avançado/fluente

Diferenciais

• Experiência no setor financeiro/fintech (reconciliação, contabilidade)
• Conhecimento em Azure Machine Learning e Cognitive Services
• Experiência com frameworks de deep learning (TensorFlow, PyTorch)
• Experiência com LLMs para entendimento de documentos (OpenAI, Azure OpenAI)

POR QUE CAPCO:

Na Capco promovemos uma cultura inclusiva. Valorizamos a diversidade em todas as suas expressões. 
Pensamos, em conjunto, sempre em ações diversas de inclusão e de responsabilidade social através de comitês internos geridos pela nossa comunidade interna, como os grupo de Mulheres, Pessoas Com Deficiência, Pessoas Negras, LGBTQIAPN+, Parentalidade, Gerações, entre outros. Nossas oportunidades são trabalhadas para todos(as)!
#LifeAtCapco

PRÓXIMOS PASSOS:

• Se você está ansioso(a) para progredir sua carreira conosco, candidate-se e aguarde o contato de um de nossos recrutadores!

Xometry (NASDAQ: XMTR) powers the industries of today and tomorrow by connecting the people with big ideas to the manufacturers who can bring them to life. Xometry’s digital marketplace gives manufacturers the critical resources they need to grow their business while also making it easy for buyers at Fortune 1000 companies to tap into global manufacturing capacity.

Xometry is looking for a Machine Learning Engineer II who is excited about advancing machine learning capabilities and bringing models into production at scale. In this role, you’ll design, deploy, and maintain robust statistical and machine learning models, working closely with data scientists to translate research and experimentation into reliable, high-impact systems. You’ll apply strong data intuition and engineering judgment to improve model performance, reliability, and observability, while building predictive models that support pricing, cost estimation, and sourcing recommendations.

What You'll Do:

• Design, build, and optimize machine learning models to enhance Xometry’s platform and business operations.
• Analyze large datasets to extract meaningful patterns and insights.
• Collaborate with cross-functional teams to integrate machine learning models into production systems.
• Learn and apply best practices in model evaluation, performance tuning, and deployment.
• Influence technical direction by identifying opportunities to improve modeling approaches, data quality, and system architecture.
• Work across teams to ensure machine learning solutions are explainable, maintainable, and aligned with business goals.
• Help bridge the gap between research and production, ensuring models perform just as well in the real world as they do in notebooks.
• Gain exposure to cutting-edge machine learning frameworks, tools, and techniques used in the manufacturing industry.

Qualifications:

• A bachelor’s degree is required, but an advanced degree (M.S. or PhD) in computer science, machine learning, AI, or a related field is highly preferred.
• Experience deploying and maintaining machine learning models in production environments.
• 4+ years of experience in machine learning, focusing on data engineering and/or data science.
• Proficient in Python, including key libraries such as PyTorch, TensorFlow, pandas, and numpy.
• Strong background in probability, statistics, and optimization techniques relevant to generative modeling.
• Familiarity with cloud computing resources and tools for model training and deployment (e.g., AWS SageMaker).
• Familiar with software engineering principles, including version control, reproducibility, and continuous integration.
• Experience in the manufacturing, supply chain, or similar industries is a plus.

#LI-Remote

Xometry is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, or disability status.

For US based roles: Xometry participates in E-Verify and after a job offer is accepted, will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.