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Data Scientist

Company:
Stratos Solutions
Location:
Chantilly, VA
Posted:
February 17, 2026
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Description:

Data Scientist

Target Labor Category: Junior, Intermediate, Senior

Position Location: Chantilly, VA (Customer Site)

Clearance Required: TS/SCI with Polygraph

Position Overview

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.

About Stratos Solutions

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.

Responsibilities

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:

Advanced Analytics & Data Exploitation

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.

AI/ML Model Development & Deployment

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.

Data Engineering & Integration Support

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.

Visualization & Decision Support

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.

Software Development & Computational Innovation

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.

Required Qualifications

Education & Clearance

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

Technical & Functional Skills

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 problem-solving skills

Ability to communicate analytic results to technical and non-technical stakeholders

Desired Skills / Qualifications

Experience supporting Intelligence Community or DoD space programs (NRO experience highly desired)

Experience deploying AI/ML models in operational mission environments

Experience with big data technologies such as Hadoop, Mahout, Accumulo, Hive, Impala, Pig, or similar platforms

Experience with entity extraction, conceptual search, and natural language processing techniques

Experience with streaming analytics and real-time data processing

Experience with Palantir or similar mission analytics platforms

Experience working in high-performance computing (HPC) environments

Experience supporting data architecting and enterprise data integration strategies

Experience with DevSecOps pipelines supporting AI/ML model deployment

Familiarity with containerization and orchestration technologies (Docker, Kubernetes, etc.)

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