Suncap Technology

Senior AI Data Scientist

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior AI Data Scientist contractor based in Charlotte, NC or Dallas, TX, for a 6-month, onsite position. Key skills include statistical modeling, graph data analysis, NLP, and proficiency in Python.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
-
🗓️ - Date
December 3, 2025
🕒 - Duration
More than 6 months
-
🏝️ - Location
On-site
-
📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
Dallas, TX
-
🧠 - Skills detailed
#NLP (Natural Language Processing) #Data Analysis #HBase #ML Ops (Machine Learning Operations) #AI (Artificial Intelligence) #"ETL (Extract #Transform #Load)" #Data Science #Python #Monitoring #NER (Named-Entity Recognition) #Anomaly Detection #Clustering #ML (Machine Learning) #Libraries
Role description
Title: AI Data Scientist Contractor Location: Charlotte, NC or Dallas, TX (100% Onsite) Duration: Contract - 6 month with potential extension Must be located in Dallas or Charlotte - role is on-site 5 days/week What You'll Get to Do: • 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 What You'll Bring with You: • 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