Data Scientist
Data Scientist role at Mutual of Omaha blending traditional statistical modeling with advanced AI orchestration, building autonomous agents and conversational interfaces to power analytical workflows. Requires strong SQL, Python, and machine learning expertise.
Join Mutual of Omaha as were looking for a Data Science team who bridges the gap between traditional statistical modeling and advanced AI orchestration. In this role, you will be partner with stakeholders serving as a key designer and builder of agentic AI systems that power analytical workflows or conversational interfaces. We are looking for a problem-solver who is as comfortable writing SQL queries as they are building autonomous agents that understand the full-stack journey.
WHAT WE CAN OFFER YOU:
WHAT YOU’LL DO:
Stakeholder Translation & Technical Spec Design: Partner closely with business stakeholders to extract core needs and translate them into rigorous technical specifications for AI systems and agent behaviors.
Perform Advanced Data Manipulation: Use SQL, Python to extract and profile data from structured and unstructured sources, ensuring high-quality data inputs for both machine learning models and LLM agent contexts.
Full-Stack Logic Integration: Apply a "full-stack" mindset to AI development. You will use GitHub Workflows, GitHub CoPilot and AWS Bedrock to ensure a seamless flow of data between the backend, AI agents , and the UI, while ensuring your code is architected for automated CI/CD pipelines and stable production environments.
Build & Orchestrate AI Agents: Develop and refine autonomous AI agents using frameworks such as LangGraph to power intelligent chatbots, designing stateful, multi-step workflows that navigate complex business logic.
Design AI Systems: Design AI solutions with a "production-first" logic. While others may handle the final deployment, you are responsible for ensuring your Python-based agents are modular, and secure, leverage AWS Cloud platform.
Build for Observability: Develop evaluation frameworks and metrics to monitor the accuracy, reliability, and cost-effectiveness of AI agents and traditional statistical models.
R&D: Develop, experiment with, and refine autonomous AI agents using frameworks such as LangGraph, conducting iterative research and prototyping to evaluate new agent behaviors, orchestration patterns, and stateful workflows before scaling them into production-grade systems.
Security: Maintain and enhance package and dependency management tools such as poetry and npm to comply with corporate development standards and resolve Critical Vulnerabilities identified by automated code quality scanning tools.
WHAT YOU’LL BRING:
The DS Core: A Graduate degree in an analytical field (Math, Sta
Posted June 21, 2026