Related skills
python machine learning fraud detection llms knowledge graph📋 Description
- Build risk and fraud ML apps that impact customer workflows
- Tackle imbalanced data, sparse signals, and cold-start labels
- Innovate in feature engineering with graphs, weak supervision, LLMs
- Establish ML infra: feature services, training pipelines, serving standards
- Design knowledge graphs for entity resolution and identity use cases
- Set technical direction and scale ML efforts across Middesk
🎯 Requirements
- 5+ years of production ML in risk, fraud, credit, or trust & safety
- Shipping external-facing ML apps in risk/fraud domains
- Knowledge graph apps: building/querying signals for identity
- Entity resolution for business/individual identities (KYB/KYC/AML)
- Classification with imbalanced labels, sparse signals, cold start
- Hands-on ML infra: feature stores, model mgmt, training/serving pipelines
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