Principal Data Scientist - Omaha, Ne.

Mutual of Omaha

United States

On-site

USD 140,000 - 180,000

Full time

14 days+
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Benefits offered by this job

Annual bonus eligibility
401(k) with company match
Paid vacation and holidays

Job summary

Mutual of Omaha seeks a Principal Data Scientist specializing in Generative AI to design, build, and deploy production AI applications across business areas. You will architect agentic AI systems, implement end‑to‑end ML lifecycles, and ensure secure, scalable cloud infrastructure on AWS.

Lead with prompt engineering, data versioning, A/B testing, and governance, while mentoring junior data scientists and engineers in a collaborative, fast‑moving environment.

Qualifications

  • Bachelor’s degree or equivalent experience in a technical field.
  • 5+ years deploying and supporting full‑stack enterprise apps with AI integration.
  • Strong experience in modern AI/ML pipelines, tooling, and cloud infra.

Responsibilities

  • Lead design, development, and deployment of Generative AI applications across operational areas.
  • Architect agen­tic AI systems with tool use and workflow automation.
  • Oversee end‑to‑end lifecycle of AI/ML projects from ideation to production.
  • Develop secure, scalable AWS infrastructure with cost optimization and compliance.
  • Collaborate with stakeholders to identify high‑impact AI use cases in underwriting, customer service, claims, and risk modeling.

Skills

Generative AI
LLM applications
MLOps
AWS cloud
LangChain / LangGraph
Python
TypeScript
CI/CD
Data engineering
Data science
Fairness in AI
Experimentation
Communication

Education

Bachelor’s degree in Computer Science, Engineering, or analytical fields

Tools

Vue
TKG
SageMaker
Bedrock
Lambda
CDK
Git
SQL
CI/CD pipelines
Automated testing

Job description

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 WE CAN OFFER YOU:
  • $140,000 to $180,000, eligible for annual bonus, as applicable.
  • 401(k) plan with a 2% company contribution and 6% company match.
  • Work‑life balance with vacation, personal time and paid holidays. See our benefits and perks page for details.
  • Applicants for this position must not now, nor at any point in the future, require sponsorship for employment.
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 experimention 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.
Why Join Us?
  • Here, your skills spark progress. You’ll solve meaningful problems, collaborate with passionate teammates, and grow in a space where innovation is the norm—not the exception.
  • We value diverse experience, skills, and passion for innovation. If your experience aligns with the listed requirements, please apply!
  • If you have questions about your application or the hiring process, email our Talent Acquisition area at careers@mutualofomaha.com. Please allow at least one week from time of applying if you are checking on the status.
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