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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # SAR Imagery Analyst / Scientist Lead - **Company:** BAE Systems - **Location:** Sterling, VA, United States - **Experience:** Expert - **Salary:** $132,962.0 - $226,035.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Computer Vision, Databases, Extract Transform Load (ETL), Data Structures, Image Quality, Information Theory, Python (Programming Language), MATLAB, Machine Learning, DataOps, Stemming - **Published:** July 23, 2026 - **Apply:** https://dejobs.org/x/x/0D4C92E2A5614FA7B3B67381647489DE/job/ ## About the Role * 15 years of full-time experience as an Imagery Analyst or Image Scientist (an applicable degree may be substituted for some experience). * 6 years of SAR analysis with understanding of collection, phenomenology, image formation process, and exploitation products. * A minimum of 5 years in a leadership or supervisory role processing personnel, staffing actions and overseeing timecards where necessary. * Experience developing, testing, and evaluating new algorithms, processes, methodologies, and products using SAR imagery including using advanced processing tools, such as Python, MATLAB, Google Earth Engine, etc., to automate scientific processes of SAR imagery data to aid analysis * Experience in RNIRS, information theoretic-based image quality metrics, SAR imagery quality metrics (e.g., Integrated Sidelobe Ratio, Multiplicative Noise Ratio), and sensor metadata describing impacts of geometry on phenomenology. * Must possess experience communicating with a variety of technical and non-technical audiences on availability and capabilities of SAR imagery products, methodologies, procedures and algorithms to enhance analysis. * Must possess deep understanding of the principles of remote sensing and imagery processing and advanced exploitation methods. * Current TS/SCI security clearance with ability to obtain CI Poly Preferred Education, Experience, & Skills * Experience applying Computer Vision (CV) and machine learning (ML) techniques to SAR imagery to address intelligence problems. ## Description The SAR Imagery Scientist Lead serves as the subject matter expert in Synthetic Aperture Radar (SAR) Imagery modality, provides technical direction and conducts the research necessary to acquire and prepare imagery of the necessary quality, standards, and requirements provided by the Government. The qualified individual will develop solutions stemming from their deep experience working with imagery from a variety of sensors and platforms. The SAR Imagery Scientist will routinely provide geospatial and imagery expertise and quantitative analysis to make recommendations that improve curation and development in support of Machine Learning algorithm testing and evaluation. The Lead will also serve as supervisor of BAE Systems and partner personnel. Day-to-day tasks may include but not be limited to: * Conducting assessments of potential differences between new sensor characteristics and capabilities as compared to currently utilized platforms. * Assessing potential differences in metadata, data format, and data structure characteristics in regard to changes to databases, schemas, API s and other ETL related processes for the ingestion and movement of data when integrating into the existing data operations pipeline. * Determining how to acquire new data, potential latency associated with acquisition, data formats, and security domains. * Determining how to pre-process and standardize the data to match existing data standards or to be transformed into a usable state for labeling and model testing purposes. This may involve converting between file format types or tiling full-size images into specified sizes or geospatial bounds. * Investigating any gaps in the emerging sensor capability that may need to be supplemented by other sources. * Exploring options for coincident imagery collects from other imagery platforms (e.g. EO platforms) that align with areas of emerging sensor s collection. Determine other platforms with similar geographic and temporal coverage. * Managing time, timesheet deadlines, and report generation as needed. ## Related Videos - [Leveraging Large Language Models for Legacy Code Translation: Challenges and Solutions](https://www.wearedevelopers.com/videos/1157-leveraging-large-language-models-for-legacy-code-translation-challenges-and-solutions) - [Multilingual NLP pipeline up and running from scratch](https://www.wearedevelopers.com/videos/901-multilingual-nlp-pipeline-up-and-running-from-scratch) - [Data Science, ML & AI in the Oil and Gas Industry at NDT Global - Dr. Katja Träumner](https://www.wearedevelopers.com/videos/1308-data-science-ml-ai-in-the-oil-and-gas-industry-at-ndt-global-dr-katja-traumner) - [Building a hypercar from scratch](https://www.wearedevelopers.com/videos/607-building-a-hypercar-from-scratch) - [Robots are coming into the wild! 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