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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist SME - **Company:** Leidos, Inc. - **Location:** Earth City, MO, United States - **Experience:** Expert - **Salary:** $131,300.0 - $237,350.0 - **Contract:** Permanent contract - **Skills:** Geographic Information Systems, Artificial Intelligence, Amazon Web Services, Data Analysis, ArcGIS (Software), Computer Vision, Microsoft Azure, Big Data, Cloud Computing, Databases, Image Analysis, Distributed Systems, Geospatial Intelligence, GIS Applications, Apache Hadoop, Python (Programming Language), Machine Learning, NumPy, Object Detection, Power BI, Tensorflow, Scaled Agile Framework, SciPy, Tableau (Software), Reinforcement Learning, Spring Cloud, Pytorch, Apache Spark, Deep Learning, Pandas, Pyspark, Scikit Learn, Information Technology, Geospatial Data Abstraction Library (GDAL), Apache Kafka, Tools for Reporting, Devsecops - **Published:** September 17, 2026 - **Apply:** https://www.thejobnetwork.com/job/e2b113a6-4f1c-4c35-aa3e-5e65d7b9c59b/data-scientist-sme ## About the Role Active Top Secret/SCI clearance with the ability to successfully pass a Polygraph examination., * Bachelor's degree in Data Science, Computer Science, Geospatial Science or related field and 12-15 years of prior relevant experience or Master's with 10-13 years of prior relevant experience. May possess a Doctorate in technical domain. \n * 10+ years of professional experience in data science. \n * 5+ years of experience with GEOINT or geospatial data analysis. \n * Proven expertise in developing and implementing machine learning and AI models, particularly in context of geospatial or remote sensing. \n * Deep knowledge of geospatial analytics tools (e.g., GIS, ArcGIS), remote sensing techniques, and the application of data science in the IC. \n * Expert proficiency in Python (or similar languages) and experience with data science libraries (Pandas, NumPy, SciPy, Scikit-learn, TensorFlow, PyTorch, or equivalent tecchnologies). \n * Strong experience with big data processing tools (e.g., Spark, PySpark, Kafka, Hadoop, AWS or Azure cloud platforms). \n * Expertise in working with geospatial data formats (e.g., GeoTIFF, Shapefiles, WMS, WFS) and spatial libraries (e.g., GeoPandas, Rasterio, GDAL). \n * Advance experience in developing and operationalizing AI/ML models and algorithms for geospatial data (e.g., object detection from satellite imagery, spatial clustering, predictive analytics). \n * Strong background in data visualization and reporting tools (e.g., Tableau, PowerBI). \n * Strong leadership, communication, and collaboration skills, with the ability to work directly with senior government officials, analysts, and technical teams. \n * Excellent problem-solving and analytical skills with a demonstrated ability to translate technical challenges into actionable insights. \n, * Advanced certifications in data science or machine learning. \n * Familiarity with the customer's mission and specific geospatial intelligence challenges. \n * Expertise in advanced deep learning techniques, particularly in computer vision and image analysis for geospatial applications. \n * Experience with cloud-native applications and distributed computing in a geospatial context. \n * Familiarity with satellite data analysis, and remoting sensing models. ## Description Turn complex data into mission advantage. Join Leidos on the Chinook Program supporting our Intelligence Community customer and play a critical role in transforming massive, complex datasets into actionable intelligence and mission insights. As a Data Scientist SME, you will bring advanced analytical expertise, innovative thinking, and technical leadership to a high performing Agile engineering team delivering next generation capabilities to our Intelligence Community customer., This is an opportunity to work at the intersection of data science, artificial intelligence, machine learning, cloud technology, and national security, where your expertise can directly influence how mission users understand data, identify patterns, and make critical decisions. You will serve as a technical authority while collaborating with software engineers, DevSecOps professionals, system architects, analysts, and mission stakeholders to solve challenging problems that don't have off-the-shelf answers., n \n * Serve as the technical SME in data science and geospatial analytics, providing high-level guidance on complex technical problems related to the GEOINT mission. \n * Lead the design and development of sophisticated data science models and machine learning algorithms to analyze large, multi-source geospatial data sets (e.g., satellite imagery, sensor data, geospatial databases). \n * Apply deep knowledge of GEOINT, remote sensing, and spatial analysis to develop and implement solutions that enhance data-driven decision-making capabilities. \n * Provide strategic recommendations for leveraging new and emerging technologies, including machine learning, AI, and cloud platforms, to improve analytical workflows, efficiency, and mission outcomes. \n * Mentor and train junior data scientists and analysts, ensuring the application of best practices in data science and the development of mission-relevant expertise. \n * Work closely with GEOINT analysts, program managers, engineers, and other stakeholders to identify critical requirements, define technical approaches, and ensure that solutions align with mission objectives. \n * Conduct applied research to explore innovative data science techniques and emerging trends (e.g., deep learning, reinforcement learning, advanced geospatial algorithms) that can be applied to solve real-world intelligence problems. \n * Oversee the deployment and operationalization of data science models, ensuring they are scalable, reliable, and deliver actionable insights to GEOINT decision-makers. \n * Maintain high-quality documentation for models, methodologies, and analysis processes to support reproducibility, training, and knowledge transfer. \n ## Related Videos - [Python Data Visualization @ Deepnote (w/ PyViz overview)](https://www.wearedevelopers.com/videos/113-python-data-visualization-deepnote-w-pyviz-overview) - [Vectorize all the things! 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