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Data Scientist
MANTECH International Corporation
Springfield, USA
Full-time
Senior · 18+ years experience
Onsite
USD 163100-289400 yearly / year
Discovered 1 weeks ago
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Description & Requirements
- MANTECH seeks a motivated, career and customer-oriented Data Scientist to join our team in Springfield, VA . This is a full-time onsite position.
- The Data Scientist shall support the maintenance and implementation of the data architecture for all Program data. This position requires experience with databases, cloud architectures, and compliance with data standards. This position is responsible for maintaining data backend workflows that allow for data operations across security domains and across systems.
Responsibilities include but are not limited to
- Create the necessary infrastructure to store and process data related to emergent sensors and platforms. This includes creation of any database tables and schemas, establishing relevant data health alerts, and the setup of data pipelines to support Extract, Transform, and Load (ETL) of all data related to the emergent sensors.
- Apply knowledge of scripting tools, programming languages, standards, and software packages to build data pipelines that enable the consumption of data supporting mission needs
- Support data analytics, data cleansing, analyst workflow efficiencies, and transformation supporting Extract, Transform, and Load (ETL) capabilities
- Manage the generation, approval, and population of data into databases, ensuring that all data complies with security regulations and satisfies customer requirements.
- Conduct regular Quality Control (QC) and monitor the content to ensure it aligns to existing data standards and requirement specifications
- Assess and report the current state of compliance of data holdings in both written and oral forms; monitor data and standards changes and adjust data architecture to remain in compliance
- Maintain data availability, accuracy, consistency, and reliability for all training data operations
- Create and maintain Government directed and approved software and computing environments to enable data preprocessing work, such as creating NPEs to enable connections to external systems, setting up software environments to enable development activities, and establishing appropriate Gitlab repositories.
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