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Data Scientist

Globaldimensionsllc

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placeStuttgart home_workOn-site labelProgram Management publicAggregated job · DE

eventPublished on Oct 06, 2026 · verifiedWe confirmed on Oct 06, 2026 that it's still live

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About the job

Global Dimensions is currently seeking a Data Scientist for a position in Stuttgart, Germany , to support mission-critical data analysis and intelligence requirements. Essential Job Functions: Perform data cleaning, preprocessing, integration, and quality assurance to ensure data accuracy and usability. Conduct data analysis and prepare datasets for visualization and reporting. Develop dashboards and complex data visualizations using tools such as Tableau and Power BI. Perform routine data quality checks and identify data inconsistencies or anomalies. Apply statistical methods, hypothesis testing, and machine learning techniques to support analytical requirements. Apply AI/ML models to analyze structured and unstructured data. Utilize Activity-Based Intelligence (ABI) tools and tradecraft to support mission requirements. Communicate analytical findings and technical information clearly to stakeholders. Required Skills: Due to the sensitivity of customer related requirements, U.S. Citizenship is required. Bachelor's degree in Data Science, Data Engineering, Information Technology, Computer Science, Information Science, or a related field from an accredited institution; or Minimum 7 years of data science support experience , with a portion of the experience occurring within the last two years. Experience with Python and automated methodologies. Knowledge and experience with hypothesis testing, statistical analysis, machine learning, and training solutions. Knowledge of communication tradecraft techniques. Experience utilizing ABI tools and tradecraft . Experience with data preprocessing, integration, quality assurance, and visualization. Desired Skills:

Previous Intelligence Community (IC) experience. Experience developing dashboards using Tableau and/or Power BI . Experience applying AI/ML techniques to unstructured data analysis.

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