Role overview
Applied AI Data Scientist
hackajob on-demand focuses on matching talented contractors like you with organisations seeking specific skills for their projects. We use our platform to connect you with exciting contract opportunities and discuss projects on behalf of the companies we partner with.
Must be located in Dallas, TX or Charlotte, NC - 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
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Seniority level
Mid-Senior level
Employment type
Contract
Job function
Consulting and Finance
Industries
Financial Services, Banking, and IT Services and IT Consulting