Lead Data Scientist

The role

This person will build risk and fraud ML applications and tackle hard data problems. They will design knowledge graph solutions and establish ML infrastructure foundations.

What you will do

• Build risk and fraud ML applications in fraud, trust & safety, KYB, and compliance domains
• Work on classification problems with extreme class imbalance, sparse signals, and cold start label challenges
• Use graph-based techniques, weak supervision, LLMs, and AI agents to improve signal extraction and automate labeling
• Partner with the ML infra team to design feature services, model training pipeline, model serving standards, and orchestration
• Design and implement knowledge graph solutions using LLMs for graph construction, querying, and retrieval

Required qualifications

• 7+ years of production ML experience in risk, fraud, credit, or trust & safety
• Track record of shipping external-facing ML applications in risk, fraud, credit, or trust & safety domains
• Hands-on experience building, querying, or extracting signals from knowledge graphs
• Experience with entity resolution for business or individual identities
• Expertise in classification with imbalanced labels, sparse signals, cold start, and production version management
• Hands-on ML infrastructure experience including feature stores and model management and ML training/serving pipelines
• Comfort as a senior IC setting technical direction, mentoring peers, and establishing best practices

Nice to have

• B2B SaaS experience, ideally building ML products for enterprise customers
• ML pipeline and automation engineering experience building end-to-end training harnesses
• Experience scaling ML across multiple products or risk domains

About the company

Middesk is building the data and intelligence infrastructure that helps businesses work together with confidence. The company provides a platform for understanding businesses to help customers verify identities, onboard customers, and manage risk.