Data Scientist

• W2 candidates only – This position is open exclusively to candidates who can work on a W2 basis.
• No third-party applications – C2C/third-party submissions will not be accepted.

Job Title: Data Scientist

Location: Irving, TX (Onsite)

Education:

• Bachelor's degree in AI, Data Science, Computer Science or any other relevant field (required)
• Master's or PhD also acceptable.

Experience:

• 5–7 years of professional experience
• 2+ years of experience applying Python (NumPy, SciPy, pandas, etc.) to solve business challenges
• Experience with cloud technologies (AWS, Azure, Google Cloud, etc.)

Top 3 Critical Skills:

• Built agents in Dataiku & Snowflake Cortex (structured data) — critical
• Workflow automation in Dataiku recipes & Python (writing programming logic)
• Experience with LangGraph, Langchain, CrewAI

Technical Requirements:

• Multi-agent architecture and orchestration patterns (agent collaboration, planning, delegation, workflow orchestration)
• Reusable agent frameworks and reference architectures
• Security, access control, and governance (RBAC, personas, authorization models, guardrails)
• Auditability and compliance considerations
• Event-driven and batch processing architectures
• API and workflow integration best practices
• Agent evaluation, testing, and observability (offline/online evaluation, groundedness, relevance, hallucination detection, task success measurement)
• Automated regression testing, monitoring, observability, and performance tracking
• Human-in-the-loop workflows (approval processes, escalation paths, feedback loops, continuous improvement)
• Dataiku application development and UX (Dataiku WebApps, production-ready front-end development, enterprise adoption best practices)
• Deployment, operationalization, and scalability (deployment automation, monitoring, governance)
• Cost and performance optimization (LLM selection, latency, token consumption, operational cost management, performance tuning)
• MCP experience in multi-agent systems for Agent-to-Agent communication (desired)
• Advanced data analysis and statistical methods (regression, hypothesis testing, ANOVA, statistical process control) (desired)
• Machine learning techniques (Clustering, Logistic Regression, CART, Random Forests, SVM, Neural Networks) (desired)
• Design/development of heavy equipment (automotive, aerospace, engine, transmission, construction, mining, industrial) (desired)