SE2S
SE2S is seeking a Mathematical/Statistical Scientist who possesses a strong background in the development and application of data mining, analysis, aggregation, fusion, and visualization in order to process, analyze, and integrate raw data facilitating the production and dissemination of scientific and technical intelligence and general military intelligence relating to foreign ground forces research, development, systems, and operations. Focus of work is to contribute to data- driven all-source analysis, assessment, and decision making and implement innovative methodologies which enhance production and dissemination activities. Job Responsibilities: Processing, tagging/labeling/parsing/indexing unstructured, semi-structured, and structured classified and unclassified data sets. Developing research designs (including formulating testable questions, identifying and defining key concepts and variables and matching appropriate methods to problems.) Data project management (including cleaning and preparing data) and creating, structuring, and maintaining data sets. Data analysis (including manipulating datasets and interpreting findings using a mix of programs/environments (such as R, Python, Matlab) and techniques (e.g., text and pattern analysis, supervised and unsupervised data clustering, classification, change/anomaly detection, time-series, regression, geospatial, and/or social network analysis.) Developing process flows/visualizations and technological developmental roadmaps and capturing them in the NGIC TechWatch Tool Using text/web data analytics for establishing and expanding keyword searches and using bibliometric analysis tools to perform horizon scans and deep dives into NGIC identified S&T research fields Creating mathematical models and coding in R, Python, MatLab, and Excel Natural Language Processing Providing knowledge/familiarity of technical language Providing experience with Big Data (parallel processing power and options for handling analysis of data) Understanding the retrieval processes from databases using industry-standard query languages (e.g., SQL)bfb3568a-762b-4989-884b-a9682aa104ca