Staff Data Scientist, Watchlist
Core
Build and scale NLP models for real-time entity matching, classification, and AML risk detection in global sanctions screening.
Role type
Staff Data Scientist (NLP & Entity Resolution)
Builds
Real-time matching engine, NLP pipelines for Named Entity Recognition (NER), and multi-signal risk scoring systems for financial institutions.
Domain
Financial Crime / AML Compliance / Sanctions Screening
Deliverable
production ML models
Required skills
NLP, Named Entity Recognition (NER), Information Extraction, Entity Resolution, Graph-based methods, Python, PyTorch, spaCy, HuggingFace Transformers, SQL, Large-scale data pipelines, LLMs, Agentic AI frameworks
Preferred skills
AML/Sanctions screening experience, Multilingual NLP (non-Latin scripts), LangChain/LangGraph
Technologies
PyTorch, spaCy, HuggingFace Transformers, LangChain, LangGraph
Responsibilities
Design and scale advanced NLP models for real-time name matching; Build multi-signal risk scoring combining name similarity and entity attributes; Develop NLP systems to consolidate and deduplicate watchlist identities; Apply graph-based methods to surface indirect risk exposure; Lead technical initiatives and mentor peers on entity matching and AI approaches.
Seniority
Staff, hands-on IC with technical leadership