USAJOBS · 3 days ago

Data Scientist

Suitland, MD

Full-time

Hybrid

Senior Level

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Responsibilities

Performs advanced queries using database and analytical tools (e.g. SQL Server) and programming languages (e.g. Python, R, and Java) to analyze data and develop data-analytical visualizations.

Provides data science expertise to a wide range of highly complex initiatives and projects focused on the development of cutting-edge tools and resources to easily access, store, analyze, and exchange complex, high-quality data.

Defines data requirements and integration of enabling technologies to collect, extract, engineer, and transform data from traditional and non-traditional sources.

Analyzes a variety of data sources to provide data-driven insights to the organization to streamline processes and evaluate the effectiveness of the program operations in meeting established goals and objectives.

Designs, implements, and evaluates large, complex analytical applications, projects, and studies, applying a combination of computational and machine learning methods to new or Big Data using next generation analytical tools.

Qualification

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MathematicsStatisticsComputer ScienceData ScienceData AnalyticsData StructuresSQLRelational Database Management SystemsBig Data ProcessingHigh Performance ComputingPythonRC#JavaProgramming Languages

Required

Degree: Mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.

One year of experience at a level of difficulty and responsibility equivalent to the GS-12 in the Federal service, including participating in the planning, design, development, and implementation of data science techniques and methods; using data analytics to develop data structures, validate data sources, and evaluate data management tools; developing/querying analytical tools and data systems such as Relational Database Management Systems (RDBMS) and SQL systems; and applying Big Data processing languages, computational algorithms including High Performance Computing (HPC), and programming languages (such as Python, R, C#, Java) to develop analytical pipelines, visualizations, and solutions.