Data Scientist

Data Scientist (Agentic AI)

Join Mutual of Omaha to build agentic AI systems that bridge traditional statistical modeling with advanced AI orchestration. You will partner with stakeholders to design and deliver analytical workflows and conversational interfaces.

What you’ll do

• Stakeholder translation & technical spec design: Work with business stakeholders to extract needs and translate them into technical specifications for AI systems and agent behaviors.
• Advanced data manipulation: Use SQL and Python to extract, profile, and prepare data from structured and unstructured sources for both ML models and LLM agent contexts.
• Full-stack logic integration: Apply an end-to-end mindset, using GitHub Workflows, GitHub Copilot, and AWS Bedrock to connect backend data, AI agents, and the UI with CI/CD-ready, production-stable code.
• Build & orchestrate AI agents: Develop and refine autonomous agents using LangGraph, creating stateful, multi-step workflows for complex business logic (e.g., chatbots).
• Design AI systems for production: Ensure Python-based agents are modular, secure, and leverage AWS Cloud.
• Observability & evaluation: Create evaluation frameworks and metrics to monitor accuracy, reliability, and cost-effectiveness of AI agents and statistical models.
• R&D and prototyping: Experiment with new agent behaviors, orchestration patterns, and stateful workflows before scaling to production.
• Security & dependency management: Maintain and enhance dependency/package management (e.g., poetry and npm) and address critical vulnerabilities flagged by automated scanning.

What you’ll bring

• Education & experience: Graduate degree in an analytical field (Math, Stats, CS, BI, etc.) and 2+ years in an analytically driven role.
• Agentic AI expertise: 2+ years building AI agents and complex systems using LangGraph or similar orchestration frameworks.
• Full-stack awareness: Understanding of the full lifecycle from databases to application logic to conversational UI.
• Required skills: Strong Python and SQL.
• AWS fluency: Hands-on experience in the AWS LLM ecosystem (including Bedrock and SageMaker) and working knowledge of AWS Lambda.
• Statistical rigor: Strong ML/statistics background and ability to validate outputs against business benchmarks.
• Production perspective: Experience building with reliability, security, and scalability in mind.

Preferred

• Experience with AWS Bedrock Agents and action group integration.
• Ability to navigate under-defined problems and deliver robust solutions.