Data Scientist II, Applied ML

FDE Times

São Paulo

On-site

BRL 120,000 - 210,000

Full time

14 days+

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Job summary

Brex is seeking a Data Scientist in São Paulo to own the full ML lifecycle—from problem framing with stakeholders to productionization and monitoring. You will build models that reduce risk and improve customer experience, and you will collaborate with cross-functional teams including Ops, Engineering, Product, Fraud, Compliance, and Credit.

Ideal candidates have 3+ years in Data Science/ML (or 2+ with a PhD), strong Python/SQL skills, and experience deploying ML systems via APIs.

Qualifications

  • 3+ years in Data Science/ML or 2+ years with a PhD
  • End-to-end model ownership including productionization
  • Proficiency in Python and SQL, ML frameworks
  • Ability to apply statistical methods like hypothesis testing and A/B tests
  • Strong software engineering fundamentals, API integration into production
  • Excellent communication and cross-functional collaboration

Responsibilities

  • Drive Data & AI solutions from inception to deployment to manage risk and improve customer experience
  • Own the full ML lifecycle from problem identification to production monitoring
  • Collaborate with Ops, Engineering, Product, Fraud, Compliance, and Credit teams

Skills

Python
SQL
ML frameworks
Statistics
A/B testing
API development
Communication

Education

PhD in quantitative field
MSc in quantitative field

Tools

API development

Job description

Why join us

Brex is the intelligent finance platform that enables companies to spend smarter and move faster in more than 200 markets. By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly. Brex’s AI-native automation and world-class service eliminate manual expense and accounting tasks for customers so they can focus on what matters most. Tens of thousands of the world's best companies run on Brex, including DoorDash, Coinbase, Robinhood, Zoom, Plaid, Reddit, and SeatGeek.

Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We’re committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career.

Data at Brex

The Data organization develops infrastructure, statistical models, and products using financial data. Our Scientists and Engineers work together to make data —and insights derived from data — a core asset across the company. Our work is ingrained in Brex’s decision-making process, in the efficiency of our operations, in our risk management policies, and in the second-to-none experience we provide our consumers.

What You’ll Do

Our Data Scientists are responsible for the entire model development lifecycle, from conception with stakeholders, through model development and productionization, to following through to see that the desired business impact is achieved — including circling back with stakeholders to make product or strategic decisions.

Responsibilities
  • Drive Data & AI solutions from inception to deployment to efficiently manage risk and/or improve customer experience.
  • Be responsible for the full machine learning lifecycle — problem identification, model design, training, productionization, and monitoring.
  • Partner with cross-functional teams (Ops, Engineering, Product, Fraud, Compliance, and Credit).
Requirements
  • 3+ years of experience in Data Science/ML roles, or 2+ years with a PhD in a quantitative field
  • Demonstrated ability to own end-to-end model development, including productionization
  • Expertise in Python programming, SQL queries, and ML-related frameworks
  • Ability to apply statistical techniques such as hypothesis testing and A/B testing, and to approach problems with a statistical mindset
  • Strong software engineering fundamentals, including experience with API development and integrating ML systems into production services
  • Strong communication skills and the ability to collaborate with various stakeholders, both technical and non-technical
Nice to Have
  • Experience working with real-time models
  • Advanced degree (MSc/PhD) or published research in Machine Learning or a related field
  • Previous experience in the risk domain (fraud, AML, and/or credit) or building customer-facing ML models (suggestions/automations)
  • Experience in the fintech industry
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