Note: The job is a remote job and is open to candidates in USA. SentiLink provides identity verification and risk solutions for detecting fraud and managing financial risk. The Quantitative Researcher will develop, analyze, deploy, and maintain machine learning models for fraud detection and identity verification, while researching new fraud types and delivering production-ready code and analyses across the full data science lifecycle.
Responsibilities
- Develop and maintain SentiLink’s fraud detection models through the full model development lifespan: from data acquisition decisions through featurization, focusing labeling resources, model training, experimentation, productionalization, and monitoring
- Build foundational modeling to drive SentiLink’s expanding suite of Fraud and Financial Risk products
- Research new types of fraud and develop new SentiLink products around identity verification
- Achieve success by researching / developing through iteration, integration of new data sources and inventive feature engineering
- Write production-ready code that can be relied on for real-time decision making by our partners
- Design, perform, and present analyses that will inform data acquisition, product development, risk operations priorities, marketing, and sales efforts
- Work with engineering, risk operations, and data acquisitions to access necessary data, maintain data quality, and support data access
Skills
- Bachelor's, Master's, or PhD in Statistics, Computer Science, Physics, Mathematics, or 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
- Demonstrated ability to analyze complex problems and build data-driven solutions
- Strong communication skills and ability to explain technical ideas clearly
- Interest in learning deeply about fraud, identity, and financial risk systems
- Ability to write clean, maintainable code
- Strong attention to detail and curiosity about real-world data problems
- Candidates must be legally authorized to work in the United States and must live in the United States
- Thrive in a fast paced environment characterized by the need to solve extremely varied, high impact, open ended problems
- This role can be remote within the U.S., with a strong preference for candidates who can work from our Austin, San Francisco, or New York offices
Benefits
- Equity
- Employer paid group health insurance for you and your dependents
- 401(k) plan with employer match (or equivalent for non US-based roles)
- Flexible paid time off
- Regular company-wide in-person events
- Home office stipend
Company Overview