Applied ML Scientist, New Grad

Responsibilities

• Develop and maintain fraud detection models through the full model development lifecycle, including data acquisition, featurization, labeling, training, experimentation, productionization, and monitoring.
• Build foundational models for Fraud and Financial Risk products.
• Research new types of fraud and develop identity verification products.
• Integrate new data sources and create inventive features through iterative research and development.
• Write production-ready code for real-time decision-making.
• Design, perform, and present analyses informing data acquisition, product development, risk operations, marketing, and sales.
• Collaborate with engineering, risk operations, and data acquisition teams to access data, maintain data quality, and support data access.

Requirements

• Bachelor's, Master's, or PhD in Statistics, Computer Science, Physics, Mathematics, a related quantitative field, or equivalent experience/research.
• Strong foundation in machine learning, statistics, or applied data science.
• Experience with Python and common data science tools through coursework, research, internships, or personal projects.
• Ability to analyze complex problems and build data-driven solutions.
• Strong communication skills and ability to explain technical ideas clearly.
• Interest in fraud, identity, and financial risk systems.
• Ability to write clean, maintainable code.
• Strong attention to detail and curiosity about real-world data problems.
• Legal authorization to work in the United States and residence in the United States.
• Ability to thrive in a fast-paced environment solving varied, high-impact, open-ended problems.

Compensation and Benefits

• Salary: $180,000–$220,000 per year, plus equity and benefits.
• Employer-paid group health insurance for employees and dependents.
• 401(k) plan with employer match.
• Flexible paid time off.
• Regular company-wide in-person events.
• Home office stipend.