Staff Data Scientist, CX (Remote)
San Francisco, California, United States
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. In collaboration with our engineering, operations, and CX teams, the data scientists build systems that help our CX agents better serve our customers.
- 8+ years in a data science role
- Expertise with SQL queries and with statistical packages, such as R and Python
- Production machine learning experience and proficiency with deploying apps in Python
- 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
- Experience with developing algorithms for the CX domain space
- Experience with Natural Language Processing (NLP) techniques