Staff Data Scientist: Real-Time Watchlist & AML NLP

Socure; Sacramento (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Socure is hiring a Staff Data Scientist to join the Watchlist Data Science team. You will advance entity matching, NLP-based information extraction, and production-grade ML systems to support global AML/sanctions screening for banks and fintechs.

You will scale real-time matching, enrich data with multilingual NLP, and drive end-to-end research-to-production initiatives with broad technical ownership and impact.

Qualifications

• Master’s or PhD in CS, Computational Linguistics, Statistics, Applied Mathematics, or related field
• 7+ years in data science or ML with NLP, entity resolution, or information extraction
• Experience in AML, sanctions screening, or financial crime detection preferred
• Hands-on NLP pipelines for entity extraction, named entity recognition, and record linkage at production scale
• Multilingual NLP and non-Latin script processing is a strong plus

Responsibilities

• Improve data quality, coverage, and freshness of Watchlist data via ingestion pipelines
• Design data quality analyses to ensure high-fidelity inputs for model training
• Develop NLP to classify and enrich raw data into normalized schemas
• Expand multilingual capabilities for global screening across scripts
• Build and improve NLP systems for deduplication and canonical profiling
• Develop and maintain risk scoring and benchmarking frameworks

Skills

NLP

Entity resolution

Information extraction

Python

ML libraries

SQL

LLMs

Data science

Education

Master’s or PhD in Computer Science or related field

Tools

PyTorch

spaCy

HuggingFace Transformers

LangChain

LangGraph

Job description

Socure is hiring a Staff Data Scientist to join the Watchlist Data Science team. You will advance entity matching, NLP-based information extraction, and production-grade ML systems to support global AML/sanctions screening for banks and fintechs.

You will scale real-time matching, enrich data with multilingual NLP, and drive end-to-end research-to-production initiatives with broad technical ownership and impact.