> Markdown version of [/jobs/ext/2989770-data-scientist-iv](https://www.wearedevelopers.com/jobs/ext/2989770-data-scientist-iv). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist IV - **Company:** Eliassen Group - **Location:** Greenwood Village, CO, United States - **Experience:** Expert - **Salary:** $145,600.0 - $166,400.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Artificial Intelligence, Amazon S3, Automation of Tests, Continuous Integration, Information Engineering, Data Security, Distributed Computing Environment, Python (Programming Language), Machine Learning, Object-Oriented Software Development, Standard Sql, Software Deployment, Software Engineering, Computer Network Operations, Large Language Models, Apache Spark, Boto3, Data Lakes, Git Flow, Information Technology, Low-code, Restful APIs, Software Version Control - **Published:** September 18, 2026 - **Apply:** https://www.dice.com/job-detail/01feebc9-fdee-43e4-8bf4-a218636bc512 ## About the Role * Strong communication and collaboration skills. * Strong software engineering fundamentals with object-oriented programming. Python preferred; Scala or Java acceptable. * Hands-on experience with distributed computing frameworks such as Spark. * Proven experience building AI agents programmatically using frameworks such as LangGraph or equivalent. No-code or low-code experience alone is not sufficient. * Understanding of LLMs and agentic patterns including multi-step reasoning, tool calling, retrieval, memory, and orchestration. * Experience with prompt and context engineering. * Demonstrated evaluation of model or agent quality including dataset design and correctness criteria beyond automated LLM-as-a-judge. * Production deployment experience with version control, automated testing, and reproducible behavior. * Experience with AWS services such as S3 and Athena and working with data at scale. * Strong SQL and structured data skills. * Experience with Git-based workflows. * Preferred: experience with LangSmith for evaluation and tracing, MCP server integrations, CI/CD deployments, LLM-as-a-judge metrics, telecom or large-scale network operations, network data sources, n8n or similar orchestration, REST APIs, cloud SDKs such as boto3, and modular code practices. Education Requirements: * Bachelor's degree in Computer Science, Mathematics, Statistics, Engineering, or related field, or equivalent experience. * Related experience: 5+ years with a bachelor's degree, or 3+ years with a master's degree in data science, machine learning, or agent/software development. Recruitment Transparency Notice ## Description * Design, build, and maintain AI agents using code-based frameworks such as LangGraph with explicit control of state, control flow, tool integration, and prompts. * Enhance and maintain multiple agents including Structured Investigation, recommendation, Data Lake Exploration, and conversational agents for Network Engineering and NSOC. * Integrate agents with anomaly detection outputs, the IIA Data Lake, and real-time sources via MCP servers. * Deploy agents to production through CI/CD pipelines, coordinating containerization and gateway integration. * Design and execute supervised evaluations by building gold standard datasets with network SMEs and measuring agent correctness. * Instrument and analyze agent behavior using tracing and observability tools such as LangSmith to diagnose failures and improve quality. * Apply prompt and context engineering to improve reasoning, accuracy, and reliability. * Ensure production standards including version control, automated testing, and deterministic, reviewable control flow. * Collaborate with Data Engineering, Anomaly Detection, and Platform Engineering on data access, workflows, and infrastructure. * Support autonomous remediation use cases in partnership with Network Engineering and NSOC. * Document designs, evaluation methods, and results for varied technical audiences. * Continuously evaluate frameworks, evaluation approaches, and tooling. ## Related Videos - [AI Agents Graph: Your following tool in your Java AI journey](https://www.wearedevelopers.com/videos/1550-ai-agents-graph-your-following-tool-in-your-java-ai-journey) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) - [Reimagining app development with Low-code and AI](https://www.wearedevelopers.com/videos/1651-reimagining-app-development-with-low-code-and-ai) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Why Git Still Matters](https://www.wearedevelopers.com/videos/100288-why-git-still-matters) - [What If Apps Built Themselves? 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