Data Scientist

Data ScientistGRVTY is seeking a motivated and experienced Data Scientist to perform data analysis via statistical and quantitative methods, develop visualizations to support decision making, and build software to enable thorough monitoring and management of data pipeline tasks. The ideal candidate brings deep expertise in data systems and a passion for solving complex analytical problems in support of Machine Learning model development and operational intelligence missions. This role will help accelerate the implementation of the NGA Maven Data Strategy and drive cross-departmental collaboration to enhance workflows and deliver greater productivity across labeling and imagery curation efforts.What You'll be OwningIntegrate emerging sensors and platforms into existing data pipelines and workflows, including:Developing pipelines and relevant data structures for emerging capabilitiesIncorporating new data types into existing data workflowsAssess potential differences in metadata, data format, and data structure characteristics regarding changes to:Databases and schemasAPIs and other ETL-related processesIngestion and movement of data within the existing data operations pipelinesConduct analysis of how emerging data impacts overall program data holdings from the perspective of:Machine Learning model developmentTest and evaluation use casesReal-world operational use casesEvaluate and recommend solutions for partitioning new data types into training, test, and validation splits for effective ML model development and performance evaluationLead the design and application of methods to identify, collect, process, and analyze large volumes of data to build and enhance products, processes, and systemsLead projects using advanced mathematical, statistical, and scientific techniques to:Examine complex mission and operational problemsCreate insights from dataBuild web scraping algorithms for imagery curation in accordance with customer data prioritiesIntegrate multiple data and intelligence sources in various formats for imagery curation to address gaps and meet project prioritiesSupport data analytics, data cleansing, analyst workflow efficiencies, and ETL transformation capabilitiesUtilize statistical and analytic methods to support answering intelligence requirements and mission objectivesBuild and integrate analytic tools and algorithms for imagery curation, acquisition, and chippingDesign methods and mechanisms to track, report, and monitor mission-specific objectives to maintain custody of training data prioritiesBuild software tools to manage labeling campaigns, including:Tracking unlabeled and labeled data and campaign statusTransferring label task information via API-based movement between platformsBuild software tools to:Filter and visualize data geospatiallyAllow feedback entry and data analysisIntegrate with existing data management platformsConduct analysis of overall data holdings to support development of performant AI/ML models satisfying operational user requirementsEvaluate, monitor, and provide recommendations on training, test, and validation data splits for effective model development and performance evaluationWhat You Must HaveActive TS/SCI Clearance with the ability to obtain a CI/PolyExperience working with AI/ML technologies and data systemsExperience working with multiple file types including:Geospatial file formatsJSON, XML, and related formats3+ years of experience in quantitative analysis and data operations, including:Developing visualizations and processing complex data to create data-driven insightsData manipulation and ETL proceduresWorking knowledge of SQL and NoSQL database technologiesDevelopment experience in Python and other languages for data cleaning and manipulationWhat Would be Nice to HaveExperience applying Natural Language Processing (NLP) algorithms to extract data from documentsExperience with enterprise NGA analytic modernization efforts such as SOM, Computer Vision, automated collection, or automated reporting, along with data standardization best practicesDemonstrated expertise in math, statistics, and quantitative analysis, including analytic techniques such as classification, regression, clustering, data reduction, and causal modeling