Data Scientist

VTG • Chantilly, VA

8h

About The Position

We are seeking an Data Scientist will provide development services in support of mission-critical functions.

What will you do?

Design, build, and maintain scalable data infrastructure and pipelines.
Develop ETL and ELT workflows to transform and prepare data for analytics and reporting.
Ensure data quality, integrity, governance, and security across data environments.
Design and operate robust data layers integrating local, cloud, and web-based data sources.
Construct complex multi-source queries using database technologies such as PostgreSQL, MySQL, Neo4J, or AWS RDS.
Process structured and unstructured data sources for downstream analytics and machine learning applications.
Develop data ingestion pipelines using Apache NiFi to centralize data environments.
Implement monitoring and optimization strategies for data systems and pipelines.
Develop reusable, tested, and reproducible code and data workflows.
Utilize Python, SQL, Linux, and Bash scripting for data engineering and automation tasks.
Work with version control systems such as Git to manage code repositories.
Use Jupyter Notebooks for data exploration, analysis, and model development.
Apply machine learning techniques, including natural language processing, to solve analytical problems.
Deliver results to stakeholders through written documentation, technical reports, and oral briefings.
Document code, data models, Python packages, and technical methodologies.
Collaborate with multiple stakeholders, including engineers, analysts, and leadership teams.
Mentor junior data scientists and engineers by explaining complex technical concepts in verbal, written, and visual formats.

Requirements

• Active TS/SCI with Polygraph required.
• Bachelor’s degree in Geospatial Intelligence, Geography, Remote Sensing, Intelligence Studies, Engineering, or related field, or equivalent experience
• Demonstrated experience in data engineering, including building data pipelines, infrastructure, and data integration solutions.
• Proficiency in Python programming for data processing and analytics.
• Strong SQL expertise and experience querying relational and non-relational databases.
• Experience working in Linux environments with advanced Bash scripting.
• Experience developing scalable ETL/ELT pipelines for analytics and reporting.
• Experience with data management and integration across multi-source environments.
• Experience using Apache NiFi for data ingestion and pipeline development.
• Experience using Git-based code repositories.
• Experience processing structured and unstructured datasets.
• Strong documentation and communication skills, including briefing technical and non-technical stakeholders.
• Experience developing tested, reusable, and reproducible analytical workflows.

Nice To Haves

• Experience with ElasticSearch and Kibana technologies.

Responsibilities

• Design, build, and maintain scalable data infrastructure and pipelines.
• Develop ETL and ELT workflows to transform and prepare data for analytics and reporting.
• Ensure data quality, integrity, governance, and security across data environments.
• Design and operate robust data layers integrating local, cloud, and web-based data sources.
• Construct complex multi-source queries using database technologies such as PostgreSQL, MySQL, Neo4J, or AWS RDS.
• Process structured and unstructured data sources for downstream analytics and machine learning applications.
• Develop data ingestion pipelines using Apache NiFi to centralize data environments.
• Implement monitoring and optimization strategies for data systems and pipelines.
• Develop reusable, tested, and reproducible code and data workflows.
• Utilize Python, SQL, Linux, and Bash scripting for data engineering and automation tasks.
• Work with version control systems such as Git to manage code repositories.
• Use Jupyter Notebooks for data exploration, analysis, and model development.
• Apply machine learning techniques, including natural language processing, to solve analytical problems.
• Deliver results to stakeholders through written documentation, technical reports, and oral briefings.
• Document code, data models, Python packages, and technical methodologies.
• Collaborate with multiple stakeholders, including engineers, analysts, and leadership teams.
• Mentor junior data scientists and engineers by explaining complex technical concepts in verbal, written, and visual formats.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 1,001-5,000 employees