Senior Data Scientist, Risk

Engineering at Brex

The Engineering team includes Data, IT, Security, and Software, and is responsible for building innovative products and infrastructure for both internal and external users. We have multiple autonomous and collaborative teams who are eager to learn, teach, and constantly improve how things work. Together, we strive to build robust and scalable systems that enable Brex to grow rapidly and help our customers reach their full potential.

Risk Data Science at Brex

The Risk Data Science team leverages data and AI to manage financial risk (fraud, money laundering, and credit), striking a balance between mitigating those risks and creating a positive experience for our customers.

What you’ll do

Our Data Scientists are responsible for the entire model development lifecycle from conception with stakeholders, developing the model in a notebook, putting it into production, and circling back with stakeholders to make product or strategic decisions. 

Where you’ll work

This role will be based in our Sao Paulo office. You must be willing to work in office at least 2 days per week on Wednesday and Thursday, starting the week of September 1st, 2025. in our Sao Paulo office. Employees will be able to work remotely for up to 4 weeks per year.

Responsibilities

• Design, develop, and deploy data and AI solutions to efficiently manage credit and fraud risk.


• Take ownership of the full machine learning lifecycle, from engineering data pipelines and feature creation to model development, deployment, and ongoing performance monitoring.


• Build and scale machine learning platforms that enable real-time risk assessment and decision-making.


• Collaborate closely with cross-functional teams (Ops, Engineering, Product, Fraud, Compliance, and Credit) to integrate AI-driven solutions into core business processes.

Requirements

• 4+ years of experience in Data Science/ML roles, with a proven track record of deploying models into production.


• Expertise in Python programming, SQL queries, and ML-related frameworks.


• Hands-on experience in credit risk modeling, underwriting, fraud or related areas, with direct exposure to building and deploying models end-to-end.


• Strong communication and interpersonal skills.


• English proficiency/fluency, both written and spoken (note: interviews will be conducted in English).


• Must be willing to work in-office 2 days per week (Wednesday and Thursday) starting September 1st, 2025, when we open our São Paulo office.

Bonus points

• Experience with real-time data sets and building scalable ML solutions.


• Experience in the finance industry, particularly in lending or credit risk.


• Experience with Deep Learning / Deep Reinforcement Learning techniques.

Location

• Must be working in Brazil at the start of role