Note: The job is a remote job and is open to candidates in USA. The company is a fast-growing technology company developing identity verification, fraud detection, and financial risk solutions. The Full-Stack Data Scientist will develop and maintain fraud detection models across the full data science lifecycle, write production-quality code, research emerging fraud patterns, and deliver analyses that inform product, operational, and commercial decisions.
Responsibilities
- Develop and maintain fraud detection models throughout the complete model lifecycle
- Inform data acquisition, labeling, feature development, model training, experimentation, deployment, and monitoring decisions
- Build foundational models for new fraud and financial risk products
- Research emerging forms of fraud and identify opportunities to develop new identity verification capabilities
- Improve model performance by integrating new data sources and developing inventive features
- Write reliable, production-quality code used for real-time decision-making
- Design, conduct, and present analyses that inform product development, risk operations, data acquisition, marketing, and sales
- Partner with engineering, risk operations, and data teams to access necessary information and maintain data quality
- Communicate project progress, technical findings, and recommendations to senior stakeholders
- Develop deep expertise in identity fraud and financial risk
Skills
- A relevant PhD with at least two years of applicable professional experience, or a relevant master's degree with at least four years of experience
- A strong track record of solving complex or high-profile business problems using data science or machine learning
- Strong practical knowledge of machine learning and statistics
- Experience owning end-to-end data science projects, from planning and defining success metrics through delivering production systems, analyses, or strategic recommendations
- Experience writing production code and automated tests
- Ability to communicate technical outcomes clearly to senior leaders and cross-functional stakeholders
- Strong attention to detail and sound judgment when making high-impact decisions
- Experience working in a startup environment
- Interest in developing deep domain expertise; previous fraud experience is not required
- Ability to thrive in a fast-paced environment and solve varied, high-impact, open-ended problems
- Must live in the United States and be legally authorized to work in the United States
- Experience with identity verification, fraud detection, fintech, financial services, or an adjacent industry
- Familiarity with advanced or state-of-the-art machine learning techniques
Benefits
- Equity
- Employer-paid health insurance for employees and their dependents
- 401(k) plan with employer matching
- Flexible paid time off
- Home-office stipend
- Regular company-wide in-person events
- Remote workplace
Company Overview