Senior Data Scientist, Credit Science (Remote)
United States
Brex
Spend smarter with integrated corporate cards, expenses, travel, and payments — in 100+ countries.Why join us
Brex is reimagining financial systems so every growing company can realize their full potential. As the financial OS, we’re building software and services in one place—disrupting long-entrenched institutions with products and experiences that better serve the ambitions of our customers.
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, developing in a notebook, putting it into production, and circling back with stakeholders to make product or strategic decisions. The data scientists on the Credit Science team, in particular,
- Design the policies that determine which customers can be safely extended credit and how much, in collaboration with Risk and Operations,
- Research and develop the underlying credit risk models that power these policies, and
- Build the systems that automate and execute real-time credit decisions, in collaboration with Data Platform and Engineering.
Requirements
- 5+ years in a data science role (or Ph.D. in a quantitative field with 3+ years in a data science role)
- Deep understanding of how to apply statistics and modeling to solve complex business problems
- Fluency with SQL queries, Python, and statistical / ML packages
- Strong interpersonal and communication skills and having worked with different business functions
- Experience initiating and driving projects to completion with minimal guidance
- Ability to hold yourself and the team to high standards
Bonus points
- Experience with credit risk models or domain knowledge in financial space
- Production machine learning experience and proficiency with deploying apps in Python
Tags: Credit risk Engineering Machine Learning Python Research SQL Statistics
Perks/benefits: Career development
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