Quantitative Specialist — Portfolio Solutions, Nu Asset

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/  

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.

• →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

• 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

• 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