Head of Fraud and Risk Analytics

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

The Fraud and Risk Analytics team is responsible for detecting and preventing fraudulent activities that may endanger the health of the Worldcoin ecosystem. Our unique growth model of using a global network of Orb Operators to give a free share of Worldcoin to everyone on Earth leads to numerous challenges that no company has ever encountered before. Potential fraud types include large-scale incentive fraud, social engineering fraud, and presentation attacks. Therefore, sophisticated fraud and risk analytics is essential for Worldcoin’s long-term success.

About the Opportunity:

As the Head of Fraud and Risk Analytics, you will take the lead in defining Worldcoin’s overall fraud and risk analytics strategy while coordinating with many other teams across Worldcoin to establish effective cross-departmental processes to ensure the health of the Worldcoin ecosystem.

In this role you will:

• Build up and manage a high-performing team of machine learning engineers and data scientists
• Define the team’s strategy for fraud detection and prevention
• Design and implement automated fraud detection algorithms that use anonymous data generated by the Orb, by the Worldcoin app, and on-chain (Blockchain) data
• Build analytics systems that scale to thousands of Orbs and billions of users
• Lead in-depth analyses into individual fraud cases and set up appropriate monitoring
• Develop strategies to prevent fraud by proposing new product features/checkpoints
• Work with our Data Engineering team to set up the technical infrastructure necessary for collecting, processing and cleaning all relevant data
• Collaborate closely with all other stakeholders (i.e., Trust and Safety, Orb, Product, Blockchain, Market Operations, AI)

About You:

• Degree in a quantitative field like computer science, statistics, applied math, operations research or similar (advanced degrees preferred), or relevant work experience
• 8+ years of hands-on technical experience in a data science role or equivalent
• 3+ years of experience in fraud and risk analytics, or related area
• 3+ years of management experience building and leading teams
• Experience with machine learning techniques for fraud detection (e.g., autoencoders for anomaly detection)
• Skilled at managing cross-functional relationships and communicating with leadership across multiple teams
• Practically oriented and “getting-the-job-done” mindset
• Thriving in a fast-paced and continuously evolving environment 
• Basic understanding of blockchain technology a plus