Data Scientist

Overview

Data Scientist

Target Labor Category:
Junior, Intermediate, Senior

Position Location:

Chantilly, VA (Customer Site)

Clearance Required:

TS/SCI with Polygraph

Stratos Solutions has an opportunity for a Data Scientist to support an Intelligence Community (IC) Space customer in Chantilly, VA. The selected candidate will operate within a collaborative government-contractor team environment supporting advanced analytics, AI/ML model development, and large-scale data exploitation efforts across mission-critical national security programs.

This role supports programs focused on extracting mission insight from high-volume, high-velocity, and complex data sources. The successful candidate will apply advanced analytical, statistical, and computational techniques to support intelligence discovery, operational decision-making, and predictive analysis. The position requires expertise working across distributed, clustered, cloud-based, and high-performance computing environments, supporting both research and operational mission applications.

If you are passionate about enabling mission advantage through advanced analytics, machine learning, and innovative data exploitation techniques, we encourage you to apply.

Stratos Solutions delivers mission-focused engineering, acquisition, and operations support to the Intelligence Community and national security space enterprise. As an employee-owned company, Stratos combines technical excellence, operational agility, and a deep commitment to customer mission success. Our teams work at the forefront of space and intelligence innovation supporting programs critical to national security.

The Data Scientist will support government customers in designing, developing, deploying, and transitioning advanced data analytics and AI/ML capabilities across mission systems and enterprise platforms.

Responsibilities include, but are not limited to:

• Analyze structured, semi-structured, and unstructured data sources to extract actionable mission insights.
• Apply techniques including:
• Latent Semantic Indexing (LSI)
• Entity extraction and tagging
• Conceptual search and topic modeling (LDA and related techniques)
• Complex Event Processing (CEP)

• Develop and apply advanced algorithms across distributed, clustered, and cloud-based high-performance computing environments.
• Perform large-scale data processing and indexing against high-volume collections and high-velocity streaming data sources.
• Develop innovative, non-traditional analytical approaches supporting high-value intelligence and mission use cases.

• Design, develop, train, validate, and deploy machine learning and data science models.
• Support onboarding, operationalization, and transition of AI/ML models into mission environments across cloud and on-premises computing architectures.
• Perform model performance analysis, validation, and lifecycle sustainment.
• Support integration of AI/ML capabilities into mission workflows and operational decision support tools.

• Provide technical support for data integration, data architecture, and data engineering activities across applicable programs.
• Develop data pipelines and transformation workflows using data transport and transformation technologies such as:
• JSON
• XML / XSLT
• JDBC
• SOAP / REST APIs
• Support ingestion, transformation, normalization, and enrichment of multi-source datasets.

• Develop analytic visualizations and multi-dimensional interfaces to support mission understanding and decision-making.
• Use visual analytics tools such as Palantir, Microsoft Pivot, or similar platforms to present analytic results.
• Provide analytic recommendations supporting operational, intelligence, and business decision-making.

• Design and deploy advanced analytic applications using enterprise and open-source software development stacks including:
• Python, Java, Ruby, Linux-based development environments
• Windows development stacks including .NET, C#, and C++
• Utilize open-source textual processing tools such as Lucene, Solr, Nutch, Sphinx, or similar technologies.
• Apply statistical modeling, clustering, and predictive analysis techniques to complex datasets.

• Bachelor’s Degree in Data Science, Computer Science, Engineering, Physics, Mathematics, Statistics, or related technical field (Relevant experience may substitute for degree requirements)
• Active TS/SCI with Polygraph

• Experience analyzing large-scale structured and unstructured datasets
• Experience with machine learning model development and deployment
• Strong programming skills in Python, Java, or similar languages
• Experience working in distributed or cloud computing environments
• Experience developing data pipelines and working with modern data architectures
• Strong mathematical, statistical, and computational…