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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - **Company:** GEOSPATIAL CONSULTING GROUP INTERNATIONAL LLC - **Location:** Arlington, VA, United States (Remote available) - **Experience:** Experienced - **Salary:** $110,000.0 - $135,000.0 - **Contract:** Permanent contract - **Skills:** Geographic Information Systems, Application Programming Interfaces (APIs), Artificial Intelligence, ArcGIS (Software), Computer Vision, Microsoft Azure, Big Data, Network Analysis, Cloud Engineering, Databases, Data Visualization, R (Programming Language), Graph Database, Python (Programming Language), Natural Language Processing, Power BI, Azure Machine Learning, SQL Databases, Tableau (Software), Unstructured Data, Enterprise Software Applications, Feature Engineering, Data Ingestion, Model Validation, Jupyter, Gitlab, Containerization, AI Platforms, Kubernetes, Information Technology, Document Classification - **Published:** September 22, 2026 - **Apply:** https://www.juju.com/job/16_bb423cf9 ## About the Role * 5 years of experience with a Bachelor's degree in Geography, GIS, Computer Science, Engineering, or related field; or 3 years of experience with a Master's degree; or 2 years of experience with a PhD. * Demonstrated professional experience with machine learning and data science techniques, including model development, evaluation, and deployment. * Proven experience with big data processing and analytics. * Experience with graph databases and graph analytics for relationship modeling and entity resolution. * Strong programming and scripting skills in Python, R, and SQL. * Experience building and running containerized applications and APIs, including deployment to Kubernetes clusters. * Proficiency with data science and analytics environments and tools such as Jupyter Lab, VS Code, GitLab, and related platforms. * Excellent written and verbal communication skills, with the ability to present complex technical concepts clearly to non-technical audiences. * Demonstrated attention to detail, analytical rigor, and accuracy. The following are preferred of the Data Scientist: * Familiarity with ArcGIS, GIS data, or spatial analytics, including integration of geospatial data into analytical workflows. * Experience with Azure AI services, Azure Foundry, or equivalent cloud-native AI platforms. * Experience integrating analytics into enterprise systems, including secure or classified environments. * Experience with ArcGIS, Power BI, Tableau, or similar visualization platforms beyond basic reporting. ## Description * Design, develop, and deploy machine learning and data science workflows, including supervised and unsupervised models, to extract insights from structured and unstructured data. * Perform content extraction and enrichment from diverse data sources and formats, including files, databases, APIs, and enterprise systems. * Apply natural language processing (NLP) and computer vision techniques for tasks such as entity recognition, entity de-duplication, keyword extraction, document classification, and similarity analysis. * Design and implement graph-based data models and analytics, supporting relationship discovery, entity resolution, and network analysis; integrate with GIS platforms where applicable. * Leverage cloud-native AI and analytics services, with emphasis on Microsoft Azure, including Azure AI services and Azure Foundry, or equivalent platforms. * Perform big data processing and analytics, including data ingestion, transformation, feature engineering, and model evaluation at scale. * Develop data visualizations and analytical products using tools such as Esri ArcGIS, Power BI, Tableau, or equivalent platforms to communicate findings to technical and non-technical audiences. * Write clean, maintainable, and well-documented code in Python, R, SQL, or related languages, using modern development practices. * Collaborate with GIS analysts and mission stakeholders to integrate analytics into operational workflows. * Produce clear technical documentation, analytical reports, and briefings; present findings effectively to stakeholders with varying technical backgrounds. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Kubernetes dev is fun, but setup and ops isn't! 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