About Verisoul
Verisoul catches fake accounts, AI bots, and fraud. We distinguish real humans from bots and bad actors for companies like P&G, Qualtrics, Clay, and VSCO.
Our Trajectory (Last 12 Months):
- 9x YoY Growth: 9x ARR growth to $5.8M, scaled from 35 to 150+ customers.
- Product Dominance: 92% competitive win rate.
- Strong Backing: Raised $8.8M Series A.
You and Your Role
Build the deep memory of the system. Analyze history, reputation, and patterns to catch sophisticated fraud that real-time checks miss.
What You’ll Do:
- Architect Reputation Systems: Build batch and nearline pipelines to score risk across identity attributes (email, phone, ISP) and lay the foundation for a scalable intelligence knowledge graph.
- Deploy Graph Analytics: Use network science—including centrality, community detection, and embeddings—to detect synthetic accounts and visualize complex fraud clusters.
- Develop Probabilistic Models: Engineer scoring algorithms that integrate historical reputation data and quantify uncertainty for dynamic entities like residential IPs.
- Innovate & Mine Data: Conduct open-ended discovery on terabytes of historical data to invent new features and uncover evolving patterns in fraud network organization.
What You’ll Bring:
- Experience: 4+ years as a full-stack engineer
- Big Data Engineering: Experience with batch processing, data pipelines, and warehousing.
- Entity Resolution: Understanding of how to link data points (email, IP, device) into a cohesive identity.
- Mathematical Intuition: You understand probability, entropy, or graph theory and can apply them to messy real-world data.
- Location: In-person in Austin, TX.
Who You’ll Work With:
- Engineering Team: To define the logic behind risk scores.