Principal Data Scientist - Omaha, NE.Job no: 505317
Work type: Full Time Regular
Location: Nebraska, Remote
Categories: Information Technology
We're currently seeking a
Principal Data Scientist specializing in Generative AI to lead the transformation of our business through the design, development, and deployment of cutting-edge, production-ready AI applications. You will architect and ship agentic AI systems that transform how our operational areas work, including applications that can reason over business context, take action through tools and integrations, and automate complex workflows end to end. This role calls for a hands-on builder with deep experience taking LLM applications from prototype to production, supported by strong full-stack engineering, MLOps, and cloud infrastructure skills. This position demands a proactive problem solver who thrives in ambiguity and can adapt swiftly to changing priorities, making a significant.
WHAT YOU'LL DO: - Lead the design, development, and deployment of Generative AI applications by immersing yourself in the needs of operational areas. Build empathy for business challenges and apply engineering best practices to deliver innovative, robust, and reliable AI solutions.
- Lead the design, development, and deployment of agentic Generative AI applications by immersing yourself in the needs of operational areas. Build empathy for business challenges and apply engineering best practices to deliver innovative, robust, and reliable AI solutions.
- Drive the end-to-end lifecycle of AI/ML projects, from ideation and experimentation through production deployment. Use prompt engineering, data versioning, systematic experimentation, and A/B testing to optimize performance.
- Develop and maintain secure, scalable infrastructure on AWS, with a focus on cloud resource management, cost optimization, and compliance. Prioritize security and fairness throughout the development and deployment process to protect our customers and uphold ethical standards.
- Collaborate on systems design and integration, ensuring seamless interoperability between AI systems and both modern and legacy front-end/back-end platforms. Maintain CI/CD pipelines and automated testing frameworks to support continuous delivery and operational reliability.
- Partner with business and technical stakeholders to identify high-impact use cases for generative AI in underwriting, customer service, claims, and risk modeling, ensuring alignment with strategic goals.
- Implement and promote MLOps best practices, enabling reproducibility, scalability, and model governance throughout the development lifecycle.
- Lead delivery using agile methodologies, incorporating continuous feedback and fostering a culture of experimentation and iterative improvement. Own your solutions from prototype through production.
- Stay informed about emerging trends in Generative AI, cloud-native technologies, model governance, and responsible AI, and apply them to deliver long-term business value.
- Mentor junior data scientists and engineers, promoting best practices in AI development, documentation, and cross-functional collaboration.
WHAT YOU'LL BRING: - Bachelor's degree in Computer Science, Engineering, or analytical fields (Mathematics, Data Science, etc.), or equivalent experience, with at least 5 years deploying and supporting full-stack applications in enterprise environments, and several years of experience integrating AI, MLOps into full-stack applications.
- Experienced in designing and shipping production Generative AI-based applications with agentic architectures, with strong skills in prompt engineering, orchestration frameworks (e.g., LangChain, LangGraph, or similar), tool/function calling, structured outputs, model selection, and LLM evaluation.
- Experienced in full-stack development (backend, frontend, and database technologies) with expertise in technologies such as Vue and TKG, and strong skills in Python, TypeScript, git, SQL, CI/CD pipelines, automated testing, and DevOps best practices.
- Experienced in AWS services, particularly Bedrock, SageMaker, S3, Lambda, and infrastructure as code (CDK). Extensive experience applying software engineering design patterns and enterprise application architecture principles to build secure, scalable, maintainable, and cost-optimized cloud-native applications.
- Experienced in data science, machine learning techniques, and data engineering. Skilled at addressing fairness in AI development and applying experimentation and A/B testing methodologies to empirically evaluate and improve model performance.
- Strong communicator and collaborator, experienced at building partnerships in remote and ever-changing environments. Resilient and resourceful problem solver, proactive at overcoming obstacles to achieve goals. Comfortable with ambiguity and change, demonstrating high learning agility, adapting quickly to shifting priorities, and bringing clarity to undefined problems.
PREFERRED: - Advanced degree in an analytical field.
- Familiarity with single or multi-cloud agentic architecture for building LLM-based applications.
- Proven experience with MLOps and implementing automated pipelines for model and algorithm training, monitoring, versioning, deployment, and scaling in production environments.
Advertised: Oct 14, 2026 09:00 AM Central Daylight Time
Applications close: 
