Data Scientist

 

Job Title: Data Scientist 

Location-Onsite full time/Morton IL or Dallas TX

Interview-1 round- if the candidate is in Peoria area then we will do in-person otherwise Virtual

 

Job Summary

Value Technology is seeking for a Data Analyst to collect, analyze, and interpret data to support business decision-making. The ideal candidate will work with business and technical teams to identify trends, build reports and dashboards, and provide actionable insights from complex datasets.

Position’s Contributions to Work Group

• As AI continues to evolve, there is a need to quickly learn new technology and build AI Agents and use them to create alerts & automate workflows.
• Most of the company’s structured data resides in Snowflake.
• We are looking for an expert who has experience building AI Agents in Dataiku & Snowflake and using Dataiku recipes & Python for workflow automation

Typical task breakdown

• Understand the objective
• Write code in Snowflake & Dataiku to build AI Agents
• Test output and update code

Interaction with team

• Daily standup meetings

Team Structure

• Work on a project with 3 other people (includes project leader)

Work environment

• Office

Education & Experience Required:

• Years of experience: 5-7years
• Degree requirement: Bachelors in AI, Data Science, Computer Science
• Do you accept internships as job experience: Yes
• Are there past or additional job titles or roles that would provide comparable background to this role: No

Top 3 Skills

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

Additional Technical Skills

• Multi-agent architecture and orchestration patterns
• Agent collaboration, planning, delegation, and workflow orchestration
• Reusable agent frameworks and reference architectures

Security, access control, and governance

• Role-based access control (RBAC), personas, authorization models, and guardrails
• Auditability, and compliance considerations

Enterprise integrations and data access patterns

• Integration with Microsoft Teams, SharePoint, email, PDFs, and enterprise data sources
• Event-driven and batch processing architectures
• API and workflow integration best practices

Agent evaluation, testing, and observability

• Offline and online evaluation methodologies
• Groundedness, relevance, hallucination detection, and task-success measurement
• Automated regression testing, monitoring, observability, and performance tracking

Prompt engineering and agent design patterns

• Prompt optimization techniques, reusable prompts, skills, tools, and agent design frameworks

Human-in-the-loop workflows

• Approval processes for high-impact business decisions
• Escalation paths, feedback loops, and continuous improvement mechanisms

Dataiku application development and user experience

• Dataiku WebApps, user experience design, and production-ready front-end development
• Best practices for enterprise adoption and usability
• Deployment, operationalization, and scalability
• Deployment automation, monitoring, and governance

Cost and performance optimization

• LLM selection and deployment strategies
• Latency, token consumption, and operational cost management
• Performance tuning and optimization best practices
• MCP experience in multi-agent system to coordinate communication across agents (Agent to Agent)

Soft Skills

• Team player
• Good communication skills