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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Cloud Data Scientist- SOCEUR - **Company:** Caci Inc - **Location:** United States - **Experience:** Expert - **Salary:** $115,600.0 - $254,200.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Big Data, Cloud Database, CompTIA Security+, Data Visualization, Python (Programming Language), Machine Learning, NumPy, Operational Data Store, Pattern Recognition, Tensorflow, SQL Databases, Tableau (Software), Data Processing, Pytorch, Apache Spark, Pandas, Scikit Learn, Information Technology, Data Lineage, Dask, Data Management, Machine Learning Operations, Looker Analytics, Software Version Control, Software Library - **Published:** August 25, 2026 - **Apply:** https://www.clearancejobs.com/jobs/9031852/cloud-data-scientist-soceur ## About the Role Required: * Must be a US Citizen possessing an active TS/SCI security clearance. * Bachelor's degree in quantitative fields such as Data Science, Statistics, Computer Science, Mathematics, or a related discipline. * DoD 8570.01-M / DoD 8140 IAT Level II (or higher) baseline certification (e.g., CompTIA Security+, CISSP). * 5+ years of professional experience in a data science or quantitative analysis role. * Advanced proficiency in Python and SQL for complex data manipulation, modeling, and analysis. * Deep expertise with core machine learning libraries and frameworks such as Scikit-learn, Pandas, NumPy, and either TensorFlow or PyTorch. * Proven experience developing and validating predictive models and using advanced statistical techniques on real-world datasets. * Demonstrated ability to work independently, conduct extensive investigations into undefined problems, and communicate complex findings to senior leadership. * TensorFlow Developer Certificate or equivalent demonstrated expertise in a major ML framework. Desired: * Experience with big data technologies (e.g., Spark, Dask) and cloud-based data science platforms (e.g., GCP's Vertex AI Notebooks). * Familiarity with preparing and formatting data for BI and visualization tools such as Looker or Tableau. * Experience working in a multi-level security (MLS) or multi-national data environment. * Familiarity with MLOps principles and tools for model versioning and tracking (e.g., MLflow, DVC). ## Description As a CACI Cloud Data Scientist will discover and develop mission-critical insights from complex and diverse datasets to support not just US but Allied and partner organizations. This role sits inside the Special Operations Command Europe (SOCEUR) Hybrid Threat Action Platform (HTAP) program team and is responsible for employing advanced statistical and machine learning methods to identify trends, build predictive models, and provide actionable insights using various data types. The individual will focus on developing and refining analytical models against real-world operational data within a multi-level security cloud environment (IL2-IL5). The individual will work closely with Data Engineers and AI/ML Engineers to operationalize validated methods and will interact regularly with data owners and mission stakeholders from Allied, partner, and US operations., * Analyze large, complex, and often unstructured datasets to identify trends, patterns, and actionable insights that address key mission requirements. * Design, prototype, and validate machine learning and statistical models to solve complex analytical problems in areas such as predictive analysis, pattern recognition, and anomaly detection. * Clean, transform, and pre-process heterogeneous data from multiple sources to ensure accuracy, completeness, and suitability for analysis. * Collaborate with the AI/ML Engineering team to transition validated models from a research/prototype phase to a deployable state, providing clear documentation and performance metrics. * Work with Data Stewards and Data Integrators to understand data lineage, quality issues, and releasability constraints for coalition and multi-national datasets. * Present highly technical findings and strategic recommendations to both technical and non-technical stakeholders, including senior leadership, in a clear and actionable manner. * Uphold and implement Responsible AI (RAI) principles, including performing bias detection and ensuring model explainability and fairness. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Vectorize all the things! 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