Our client, a top-tier Management Consulting firm, is seeking a highly skilled Applied AI Data Scientist for a top tier US Bank. 

Responsibilities and Requirements: 

• Perform statistical analysis, clustering, and probability modeling to drive insights and inform AI-driven solutions
• Analyze graph-structured data to detect anomalies, extract probabilistic patterns, and support graph-based intelligence
• Build NLP pipelines with a focus on NER, entity resolution, ontology extraction, and scoring
• Contribute to AI/ML engineering efforts by developing, testing, and deploying data-driven models and services
• Apply ML Ops fundamentals, including experiment tracking, metric monitoring, and reproducibility practices
• Collaborate with cross-functional teams to translate analytical findings into production-grade capabilities
• Prototype quickly, iterate efficiently, and help evolve data science best practices across the team
• Solid experience in statistical modeling, clustering techniques, and probability-based analysis
• Hands-on expertise in graph data analysis, including anomaly detection and distribution pattern extraction
• Strong NLP skills with practical experience in NER, entity/ontology extraction, and related evaluation methods
• An engineering-forward mindset with the ability to build, deploy, and optimize real-world solutions (not purely theoretical)
• Working knowledge of ML Ops basics, including experiment tracking and key model metrics
• Proficiency in Python and common data science/AI libraries
• Strong communication skills and the ability to work collaboratively in fast-paced, applied AI environments