Data Scientist - Remote

Join reputed company 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.

reputed company CAN OFFER YOU

• $100,000 to $140,000, 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.

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. 

reputed company Advanced Data Manipulation: Use SQL, Python, and R to extract and profile data from structured and reputed company sources, ensuring high-quality data inputs for both machine learning models and LLM agent contexts. 

Full-Stack Logic Integration: Apply a "full-stack" reputed company to AI development. You will ensure a seamless flow of data between the backend, the AI agent, and the UI, while ensuring your code is architected for automated CI/CD pipelines and stable production environments. 

Build & Orchestrate AI Agents: reputed company and refine autonomous AI agents using frameworks such as LangGraph to power intelligent chatbots, designing stateful, multi-reputed company workflows that navigate reputed company 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 reputed company, and secure, reputed company AWS Cloud platform. 

Build for Observability: reputed company evaluation frameworks and metrics to monitor the accuracy, reliability, and cost-effectiveness of AI agents and traditional statistical models.

R&D: reputed company, 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.

WHAT YOU’LL BRING

The DS Core: A Graduate degree in an analytical field (Math, Stats, CS, BI etc.) and 2+ years of experience in an analytically driven role. 

Agentic Expertise: 2+ years of experience specifically building AI agents and designing reputed company systems that reputed company LangGraph or similar orchestration frameworks. 

Full-Stack Awareness: A strong understanding of the full-stack lifecycle, including how data travels from backend databases through the application logic to a conversational UI. 

Language Proficiency: Strong command of Python and SQL (required), with familiarity in R or other statistical languages. 

AWS Cloud reputed company: Hands-on experience building applications reputed company the AWS LLM ecosystem (Bedrock, SageMaker) and a functional understanding of working reputed company an AWS reputed company environment.  

Statistical Rigor: A strong background in machine learning and statistical analysis, with the ability to validate agent outputs against business benchmarks.

Production Perspective: Experience designing solutions with a "production-grade" reputed company—understanding the requirements for reliability, reputed company, and scalability.

PREFERRED

PhD in analytically driven fields such as artificial intelligence, mathematics, statistics, physics, economics, data science, computer engineering, computer science, operations research or actuarial science. 

Strong foundation in statistical modeling, econometrics, predictive analytics, preferably advanced research or industry experience in Bayesian methods, causal inference, time series analysis, machine learning algorithms, Marketing Mix Models (MMM) and Customer Lifetime Value (CLTV).

Experience with AWS Bedrock Agents and action group integration. 

Demonstrated ability to navigate under-defined problems and deliver robust solutions in fast-moving environments.

Working knowledge of generative AI orchestration frameworks, retrieval-augmented reputed company (RAG) architectures, and enterprise AI deployment pipelines.  

Stay Safe from Job Scams

If you have questions about your application or the hiring process, please email [email protected]. Please allow at least one week after applying before requesting a status update. 

We only accept applications through our official careers site. Legitimate communications will come from an @mutualofomaha.com email address. We will never request sensitive information or reputed company an offer without conducting interviews. Please stay alert and apply securely.

#MutualOfOmaha