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The DarkStar Group
AI

Data Scientist - Cleared

The DarkStar Group · Chantilly, VA, US

Actively hiring Posted 4 days ago
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Responsibilities

  • Design, develop, and maintain Python-based data processing pipelines and workflow orchestration solutions for large-scale text ingestion, transformation, and enrichment.
  • Develop and implement AI-powered agentic workflows and LLM-integrated applications to automate data triage, classification, analysis, and processing tasks.
  • Build, enhance, and maintain reusable AI capabilities, prompt frameworks, and agent-based services that support enterprise data analysis platforms.
  • Integrate and operationalize Large Language Models (LLMs) to deliver retrieval, reasoning, summarization, information extraction, and decision-support capabilities.
  • Troubleshoot, optimize, and scale text-processing pipelines to ensure data quality, system reliability, and efficient AI-driven workflows.
  • Design and develop APIs and backend services that connect AI models, data pipelines, and mission applications.
  • Collaborate with cross-functional teams including data scientists, software engineers, and product stakeholders to prototype, test, and deploy AI-enabled solutions.
  • Develop Python-based automation tools and services supporting data engineering, workflow orchestration, model integration, and operational efficiencies.
  • Support the deployment and maintenance of production-scale AI and machine learning solutions in mission-focused environments.
  • Evaluate emerging AI technologies and recommend enhancements that improve analytical capabilities and operational outcomes.

Basic qualifications

  • Active TS/SCI with Polygraph Clearance
  • Develop and perform ETL on large unstructured datasets.
  • Experience with Python
  • Experience with services including Apache Kafka, Apache Spark, and Prefect
  • Experience containerizing applications using Docker and deployments on Kubernetes
  • Building and maintaining CI/CD pipelines for data and platform services
  • Familiarity with Linux-based systems
  • Solid understanding of DevOps principles (automation, monitoring, reliability)

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