Data Scientist

Kani Solutions Inc; Irving (TX); On-site; USD 120,000 - 150,000; Full time

Job summary

Kani Solutions Inc. is seeking a Data Scientist to join our team in Irving, TX onsite. The role requires 5–7 years of experience, strong Python (NumPy, SciPy, pandas) skills, and cloud experience (AWS/Azure/GCP).

Candidates should hold a Bachelor's degree in AI, Data Science, CS, or related field; Master’s or PhD is a plus. The position emphasizes multi-agent architecture, data analytics, and production-ready ML development.

Qualifications

• Bachelor's degree in AI, Data Science, CS or related field required.
• Master's degree or PhD also acceptable.
• 5–7 years of professional experience.
• 2+ years of experience applying Python to solve business challenges.

Skills

Dataiku

LangChain

CrewAI

Education

Bachelor's degree in AI, Data Science, CS

Master's or PhD

Tools

Python

AWS

Azure

GCP

Job description

• 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)