Data Scientist II, Applied ML

Summary

Data Scientist on Brex's Risk Data Science team, owning the full ML lifecycle — from problem framing through productionization and monitoring — for fraud, AML, and credit risk models, partnering with Ops, Engineering, Product, Fraud, and Compliance.

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.

In the Risk Data Science team, we leverage 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, 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

Please be aware, job-seekers may be at risk of targeting by malicious actors looking for personal data. Brex recruiters will only reach out via LinkedIn or email with a domain. Any outreach claiming to be from Brex via other sources should be ignored.

What this application asks

greenhouse

First Name, Last Name, Email, Phone, Resume/CV, Cover Letter

  • LinkedIn Profile optional
  • Website or GitHub optional
  • What are your preferred gender pronouns? (She/Her/Hers; He/Him/His; They/Them/Theirs, etc.) optional
  • How did you hear about us? choose one
  • If you heard about us through a referral, please state the Brex employee's name. optional
  • What country are you based in? choose one
  • Are you authorized to work in the stated location of this role? choose one
  • If you're not authorized to work at the stated location, what sponsorship would you require for the role? optional
  • Do you currently live in, or plan to relocate to, the specified location to meet this in-office requirement? choose one
  • Do you consent to Brex processing your personal information for the purpose of assessing your candidacy for this position in accordance with Brex’s Applicant Privacy Policy? choose one
  • This role requires in-office work three days per week (Mon, Wed, Thurs). Do you acknowledge and agree to this requirement? choose one
  • Do you currently, or have you previously, worked at Capital One or a company acquired by Capital One as an employee, contractor, consultant, or temp? (For example Capital One Bank, N.A., Capital One Services, Inc., Chevy Chase Bank, Discover, Hibernia, ING Direct, North Fork Bank) choose one
  • If you currently work, or have previously worked, at Capital One or a company acquired by Capital One, please provide your Employee ID (EID). This information is required for former/current employees. optional

See also

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