Staff Data Scientist (Watchlist)

Join our team as a Staff Data Scientist, where you will tackle complex challenges in entity matching and classification. You will have a direct impact on a product that helps financial institutions manage sanctions and AML risk. Your responsibilities will include improving data quality, designing data analysis pipelines, applying NLP and AI, expanding multilingual capabilities, and developing advanced NLP models. You will also collaborate closely with Product and Engineering teams and mentor peers. This is a remote position with comprehensive benefits.

• Conception et mise en œuvre de modèles avancés de traitement du langage naturel (NLP) pour la reconnaissance d'entités nommées (NER) et l'extraction d'informations.
• Amélioration de la qualité, de la couverture et de la fraîcheur des données sous-jacentes de Watchlist grâce à des pipelines d'ingestion de nouvelle génération.
• Conception et exécution de pipelines d'analyse de la qualité des données pour identifier les anomalies, évaluer la santé des ensembles de données et garantir des entrées de haute fidélité pour l'entraînement des modèles en aval.

• Master's or PhD in Computer Science, Computational Linguistics, Statistics, Applied Mathematics, or a related field; or equivalent professional experience
• Strong proficiency in Python and major ML libraries (PyTorch, spaCy, HuggingFace Transformers)
• Strong SQL proficiency and experience with large-scale data pipelines and production ML systems
• Experience with LLMs and agentic AI frameworks (e.g., LangChain/LangGraph) is a plus
• 7+ years of experience in data science or machine learning, with meaningful work in NLP, entity resolution, or information extraction
• Excellent communication skills — able to translate model performance tradeoffs into compliance and business language for non-technical audiences
• Note: We cannot provide Sponsorship at this time
• Experience in AML, sanctions screening, adverse media, or financial crime detection is strongly preferred
• Hands-on experience building and deploying NLP pipelines for entity extraction, named entity recognition, and record linkage at production scale
• Familiarity with multilingual NLP and non-Latin script processing is a strong plus