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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},1793139929615,[],{"company":418,"job_id":419,"title":420,"slug":421,"apply_url":422,"clearance":423,"categories":424,"locations":426,"description_html":428},"GRVTY","4265081009","Data Scientist","data-scientist-uakfunp9","https:\u002F\u002Fjob-boards.greenhouse.io\u002Fgrvty\u002Fjobs\u002F4448440009","TS\u002FSCI + FS Poly",[425],"Engineering",[427],"Chantilly, VA","\u003Cp>\n    \u003Cstrong>\n        What You'll be Owning\n    \u003C\u002Fstrong>\n\u003C\u002Fp>\n\u003Cp>\n    GRVTY is seeking a Data Scientist with a TS\u002FSCI + Poly clearance (applicable to this customer) to join one of our top projects in Chantilly, VA. Support the Customer with the requirements for new system capabilities, the extension and maintenance of bulk data pipeline and enhancements for multiple applications in the customers' cloud computing environment.\n\u003C\u002Fp>\n\u003Cp>\n    \u003Cstrong>\n        What You Must Have\n    \u003C\u002Fstrong>\n\u003C\u002Fp>\n\u003Cul>\n    \u003Cli>\n        Active TS\u002FSCI with Polygraph Clearance\n    \u003C\u002Fli>\n    \u003Cli>\n        Demonstrated experience utilizing big data processing tech such as Spark, Pyspark, and Python.\n    \u003C\u002Fli>\n    \u003Cli>\n        Demonstrated experience data mapping, extraction, transformation and loading.\n    \u003C\u002Fli>\n    \u003Cli>\n        Demonstrated experience building analytic reports in tools such as CloudWatch and Kibana.\n    \u003C\u002Fli>\n    \u003Cli>\n        Demonstrated experience processing and converting of OS and Data Logs into reports and metrics Dashboards.\n    \u003C\u002Fli>\n    \u003Cli>\n        Demonstrated experience with Regular Expressions (RegEx).\n    \u003C\u002Fli>\n    \u003Cli>\n        Demonstrated experience with SQL, MySQL, PostgresSQL.\n    \u003C\u002Fli>\n    \u003Cli>\n        Demonstrated experience with Data file type processing XML, JSON.\n    \u003C\u002Fli>\n    \u003Cli>\n        Demonstrated experience with IDEs and Data Modeling through Notebooks and Visual Studio.\n    \u003C\u002Fli>\n    \u003Cli>\n        Demonstrated experience ETL’ing data from disparate structured & unstructured data formats into enriched, query-friendly structured data in indexed files.\n    \u003C\u002Fli>\n    \u003Cli>\n        Demonstrated experience performing extensive data review and data quality analysis.\n    \u003C\u002Fli>\n    \u003Cli>\n        Demonstrated experience developing ETL design documentation including source and target mapping and data dictionary information.\n    \u003C\u002Fli>\n    \u003Cli>\n        Demonstrated experience interfacing with customers and integration partners for gaining and clarifying detailed objectives.\n    \u003C\u002Fli>\n    \u003Cli>\n        Demonstrated experience supporting Agile development by contributing to tasking definition, scope and review.\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        Demonstrated experience deploying capabilities on the Databricks unified analytics platform.\n    \u003C\u002Fli>\n    \u003Cli>\n        Demonstrated experience with Elastic Map Reduce to run big data workloads.\n    \u003C\u002Fli>\n    \u003Cli>\n        Demonstrated experience in joining multiple complex data sets using Spark.\n    \u003C\u002Fli>\n    \u003Cli>\n        Demonstrated experience in tuning Spark streaming and batch jobs for cluster utilization and speed.\n    \u003C\u002Fli>\n    \u003Cli>\n        Demonstrated experience in deploying complex, notebook-based pipelines.\n    \u003C\u002Fli>\n    \u003Cli>\n        Demonstrated experience in Python data analysis libraries such as Pandas.\n    \u003C\u002Fli>\n    \u003Cli>\n        Demonstrated experience utilizing Cloud services such as Lambda, SNS\u002FSQS, or EC2.\n    \u003C\u002Fli>\n    \u003Cli>\n        Demonstrated experience with DevOps tools to include Cloudwatch, Lambda, SQS, Dynamo and RDS.\n    \u003C\u002Fli>\n    \u003Cli>\n        Demonstrated experience working with Elastic, ElasticSearch\u002FLogstash\u002FKibana (ELK stack).\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.\nWe’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.\nOur 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\u003Cp>\n    \u003Cstrong>\n        Virginia Pay Range\n    \u003C\u002Fstrong>\n\u003C\u002Fp>\n\u003Cp>\n    $150,000-$250,000\n\u003C\u002Fp>\n"]