hackajob

Applied Scientist

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an "Applied Scientist" in Dallas, TX or Charlotte, NC, on-site for 5 days/week. Contract length and pay rate are unspecified. Key skills include statistical modeling, graph data analysis, NLP, ML Ops, and proficiency in Python.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
January 15, 2026
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Charlotte, NC
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🧠 - Skills detailed
#"ETL (Extract #Transform #Load)" #Python #Anomaly Detection #Libraries #AI (Artificial Intelligence) #ML (Machine Learning) #ML Ops (Machine Learning Operations) #Monitoring #NER (Named-Entity Recognition) #NLP (Natural Language Processing) #Clustering #Data Science #HBase #Data Analysis
Role description
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