Data Scientist

Overview

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.

Do you have what it takes?

• 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 with ElasticSearch and Kibana technologies.
• 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.