RIT Solutions, Inc. · 1 month ago
Applied AI Data Scientist
New York, NY
Full-time
Onsite
Senior Level
5+ years expRIT Solutions, Inc. is a top-tier Management Consulting firm seeking a highly skilled Applied AI Data Scientist for a top tier Client. The role involves performing statistical analysis and building NLP pipelines to inform AI-driven solutions, collaborating with teams to translate findings into production-grade capabilities.
Staffing & Recruiting
No H1B
Responsibilities
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
Qualification
Required
5–8 Years of experience
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
Company
RIT Solutions, Inc.
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201-500 employees
Funding
Current Stage
Growth StageCompany data provided by crunchbase