Quick Overview
Seniority
Mid Senior
Work mode
On Site
Location
Irving, TX, United States
Posted
17 hours ago
AWSMachine LearningNumPySciPySnowflakeAzureGoogle CloudLLMPandasPython
Job Description
Job Title: Data Scientist
Location: Irving, TX (Onsite)
Hire Type: Contract (12 months+)
Work Timings: 7:00 am – 4:30 pm CDT
JOB DETAILS
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
- Enterprise integrations (Microsoft Teams, SharePoint, email, PDFs, enterprise data sources)
- 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
- Prompt engineering and agent design patterns (prompt optimization, reusable prompts, skills, tools, agent design frameworks)
- 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)
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