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Wait","2026-09-24T19:22:52","layered-defense-we-dont-need-to-wait","https:\u002F\u002Fentry.grvty.com\u002Flayered-defense-we-dont-need-to-wait\u002F",{"node":400},{"altText":17,"mediaItemUrl":401,"mediaDetails":402},"https:\u002F\u002Fentry.grvty.com\u002Fwp-content\u002Fuploads\u002F2026\u002F09\u002FLayered-Approach-v3.jpg",{"width":379,"height":380,"sizes":403},[404,406,408,410,412],{"sourceUrl":405,"width":133},"https:\u002F\u002Fentry.grvty.com\u002Fwp-content\u002Fuploads\u002F2026\u002F09\u002FLayered-Approach-v3-300x169.jpg",{"sourceUrl":407,"width":136},"https:\u002F\u002Fentry.grvty.com\u002Fwp-content\u002Fuploads\u002F2026\u002F09\u002FLayered-Approach-v3-648x365.jpg",{"sourceUrl":409,"width":139},"https:\u002F\u002Fentry.grvty.com\u002Fwp-content\u002Fuploads\u002F2026\u002F09\u002FLayered-Approach-v3-768x432.jpg",{"sourceUrl":411,"width":142},"https:\u002F\u002Fentry.grvty.com\u002Fwp-content\u002Fuploads\u002F2026\u002F09\u002FLayered-Approach-v3-1024x576.jpg",{"sourceUrl":413,"width":145},"https:\u002F\u002Fentry.grvty.com\u002Fwp-content\u002Fuploads\u002F2026\u002F09\u002FLayered-Approach-v3-1280x720.jpg",{"linkOverride":171,"outlet":292},1793137842423,[],{"company":418,"job_id":419,"title":420,"slug":421,"apply_url":422,"clearance":423,"categories":424,"locations":426,"description_html":428},"GRVTY","4265926009","Data Scientist 3","data-scientist-3-dfnzqjqx","https:\u002F\u002Fjob-boards.greenhouse.io\u002Fgrvty\u002Fjobs\u002F4449817009","TS\u002FSCI + CI Poly",[425],"Cyber",[427],"Annapolis Junction, MD","\u003Cp>\n    \u003Cstrong>\n        What You’ll be Owning:\n    \u003C\u002Fstrong>\n\u003C\u002Fp>\n\u003Cul>\n    \u003Cli>\n        We are seeking a Data Scientist to support our NLP project focused on accurate and automatic tokenization of language data from spoken or written sources. In this role, you will develop automated solutions for annotating language data with parts of speech information and enhance existing models by evaluating their performance against human-generated annotations for both speech and text. Your contributions will be crucial in advancing our NLP capabilities and ensuring high-quality language processing.\n    \u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>\n    \u003Cstrong>\n        What You Must Have\n    \u003C\u002Fstrong>\n    :\n\u003C\u002Fp>\n\u003Cul>\n    \u003Cli>\n        Bachelor’s Degree with 10 years of relevant experience\n    \u003C\u002Fli>\n    \u003Cli>\n        Associates degree with 12 years of relevant experience\n    \u003C\u002Fli>\n    \u003Cli>\n        Bachelor’s Degree must be in Mathematics, Applied Mathematics Statistics, Applied Statistics, Machine learning, Data Science, Operations Research, or Computer Science or a degree in a related field (Computer Information Systems, Engineering), a degree in the physical\u002Fhard sciences (e.g. physics, chemistry, biology, astronomy), or other science disciplines with a substantial computational component (i.e. behavioral, social, or life) may be considered if it included a concentration of coursework (5 or more courses) in advanced Mathematics (typically 300 level or higher, such as linear algebra, probability and statistics, machine learning)  and\u002For computer science (e.g. algorithms, programming, , data structures, data mining, artificial intelligence).  College-level requirement, or upper-level math courses designated as elementary or basic do not count. Note: A broader range of degrees will be considered if accompanied by a Certificate in Data Science from an accredited college\u002Funiversity.\n    \u003C\u002Fli>\n    \u003Cli>\n        Relevant experience must be in designing\u002Fimplementing machine learning, data science, advanced analytical algorithms, programming (skill in at least one high-level language (e.g. Python)), statistical analysis (e.g. variability, sampling error, inference, hypothesis testing, EDA, application of linear models), data management (e.g. data cleaning and transformation), data mining, data modeling and assessment, artificial intelligence, and\u002For software engineering. Experience in more than one area is strongly preferred.\n    \u003C\u002Fli>\n    \u003Cli>\n        Active TS\u002FSCI w\u002F poly\n    \u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>\n    \u003Cstrong>\n        What Would Be Nice to Have:\n    \u003C\u002Fstrong>\n\u003C\u002Fp>\n\u003Cul>\n    \u003Cli>\n        Employ some combination (2 or more) of the following skill areas:\n    \u003C\u002Fli>\n    \u003Cli>\n        Foundations: (Mathematical, Computational, Statistical)\n    \u003C\u002Fli>\n    \u003Cli>\n        Data Processing: (Data management and curation, data description and visualization, workflow and reproducibility)\n    \u003C\u002Fli>\n    \u003Cli>\n        Modeling, Inference, and Prediction: (Data modeling and assessment, domain-specific considerations)\n    \u003C\u002Fli>\n    \u003Cli>\n        Devise strategies for extracting meaning and value from large datasets. Make and communicate principled conclusions from data using elements of mathematics, statistics, computer science, and application specific knowledge. Through analytic modeling, statistical analysis, programming, and\u002For another appropriate scientific method, develop and implement qualitative and quantitative methods for characterizing, exploring, and assessing large datasets in various states of organization, cleanliness, and structure that account for the unique features and limitations inherent in Government data holdings. Translate practical mission needs and analytic questions related to large datasets into technical requirements and, conversely, assist others with drawing appropriate conclusions from the analysis of such data. Effectively communicate complex technical information to non-technical audiences. Make informed recommendations regarding competing technical solutions by maintaining awareness of the constantly shifting Government collection, processing, storage and analytic capabilities and limitations.\n    \u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>\n    \u003Cstrong>\n        Pay Range:\n    \u003C\u002Fstrong>\n    At GRVTY, we understand that compensation is influenced by many factors—such as geographic location, federal contract labor categories, wage rates, prior experience, skillsets, education, and certifications.We’re proud to offer a work environment that empowers our team to achieve a strong work-life balance. GRVTY provides competitive pay, comprehensive benefits, and meaningful opportunities for professional growth.Our benefits package is designed to support the well-being of our employees and their families, and includes coverage in areas such as healthcare, financial wellness, retirement planning, family assistance, continued education, and paid time off.\n\u003C\u002Fp>\n\u003Cul>\n    \u003Cli>\n        The pay range for this position is: $131000.00 - $161000.00\n    \u003C\u002Fli>\n\u003C\u002Ful>\n"]