Job ID: JOB_ID_3299
Job Overview
Seeking an AI Data Scientist to perform statistical analysis, clustering, and probability modeling to drive insights and inform AI-driven solutions. This role involves analyzing graph-structured data to detect anomalies, extract probabilistic patterns, and support graph-based intelligence. You will also 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, applying ML Ops fundamentals, including experiment tracking, metric monitoring, and reproducibility practices. Collaborate with cross-functional teams to translate analytical findings into production-grade capabilities, prototyping quickly, iterating efficiently, and helping to evolve data science best practices across the team.
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.
Special Requirements
Locals, need F2F interview. Interview process: Virtual and then F2F interview.
Compensation & Location
Salary: $130,000 – $170,000 per year (Estimated)
Location: Dallas, TX
Recruiter / Company – Contact Information
Recruiter / Employer: Upstream Global Services
Email: i@upstreamgs.com
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