Lead Data Scientist

What you'll do

• Develop production risk and fraud models for trust and safety, KYB, and compliance, and improve challenging classification and labeling workflows.
• Build knowledge graph solutions using LLMs for construction, querying, and retrieval in entity resolution and business identity applications.
• Partner with ML infrastructure teams on feature services, training and serving pipelines, model standards, and orchestration.

What they ask for

• 7+ years of production ML experience in risk, fraud, credit, trust and safety, knowledge graphs, or entity resolution.
• Experience with real-world classification challenges, including imbalanced labels, sparse signals, cold starts, and production version management.
• Hands-on ML infrastructure experience with feature stores, model management, and ML training and serving pipelines.
• Ability to set technical direction, mentor peers, and establish best practices as a senior individual contributor.

Nice to have

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

Pay

$210K – $250K USD base salary

Tools

ML, LLMs, AI agents, feature stores, knowledge graphs

AI focus

Build AI-driven onboarding and risk applications; use LLMs and AI agents for signal extraction, automated labeling, and knowledge graph construction, querying, and retrieval.