Senior Data Scientist, Risk
: Job Details :

Brex is the AI-powered spend platform. We help companies spend with confidence with integrated corporate cards, banking, and global payments, plus intuitive software for travel and expenses. Tens of thousands of companies from startups to enterprises — including DoorDash, Flexport, and Compass — use Brex to proactively control spend, reduce costs, and increase efficiency on a global scale.

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.

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.

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.

Responsibilities

• Drive Data & AI solutions from inception to deployment to efficiently manage risk
• Be responsible for the full machine learning lifecycle: data acquisition, model design, training, productionization, and monitoring
• Partner with cross-functional teams (Ops, Engineering, Product, Fraud, Compliance, and Credit)

Requirements

• 4+ years of experience in Data Science/ML roles
• Expertise with Python programming, SQL queries, and ML-related frameworks
• Previous experience in the Risk domain (Fraud, AML, and/or Credit)
• Strong communication and interpersonal skills
• Must be willing to work in office 2 days per week on Wednesday and Thursday.
• Experience working with real-time data sets
• Experience in the finance industry

Compensation

The expected salary range for this role is $176,800 - $221,000. However, the starting base pay will depend on a number of factors including the candidate's location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

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