We're seeking experienced Computer Scientists to develop data mining solutions for web applications.
Responsibilities:
Employ mathematics, statics, information science, artificial intelligence, machine learning, network science, probability modeling, data mining, data engineering, data warehousing, data compression, data protection, and / or other scientific techniques to correlate complex, technical findings into graphical, written, visual and verbal narrative products on trends of existing intelligence data to leverage other IC data sources.
Develop machine learning and data mining algorithms, including, but not limited to, Multiple Information Model Synthesis Architecture (MIMOSA) prediction algorithms based on open source capabilities.
Integrate and/or code algorithms to support Government intelligence search and discovery missions.
Make best-practice recommendations on managing data within hardware, software, storage, and bandwidth constraints.
Employ data science techniques to support predictive analysis, social media and crowd-source data analytics, wargaming, and strategy development.
Employ exploratory analysis and rapid iteration techniques of large volumes of data to quickly derive intelligence.
Prepare products to describe and document findings and activities.#divergent #902
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- Minimum 20 years' computer science experience with at least a portion of the experience within the last 2 years.
- Minimum 4 years' experience with SQL Server and SQL database development.
- Minimum 3 years' experience with Visual Basic.
- Minimum 2 years' experience with C#.
- Minimum 2 years' experience in developing scripts for extracting, transforming, and loading (ETL) mass data from diverse sources and formatting.
- Experience with developing machine learning algorithms to perform various tasks for import, analysis, notifications, and enrichment of data.
- Must possess active Security-Plus credentialing and certification.
- Must be qualified at Information Assurance Technical Workforce Requirement Level II as defined in DoD 8570.01-M.
