Data Scientist

Booz Allen Hamilton•Usa, VA

About The Position

Data Scientist The Opportunity: Join a team focused on delivering advanced intelligence, surveillance, and reconnaissance (ISR) solutions for mission-critical environments. Our goal is to leverage data science, machine learning, and semantic technologies to empower operators and decision-makers with interoperable, standards-compliant data solutions to meet emerging challenges on a global scale. We are seeking a highly skilled Data Scientist to support cutting-edge data interoperability initiatives within dynamic operational environments. This role will focus on delivering Air Force (AF), Department of War (DoW), and Intelligence Community (IC) compliant solutions for structured mission data, supporting operations through improved interoperability of data systems. You will work directly with key technical and operational stakeholders to identify challenges, develop innovative solutions, and operationalize data workflows to meet mission requirements.

Requirements

3+ years of experience with Python and performing exploratory data analysis (EDA) tasks, including anomaly detection techniques
3+ years of experience with solution development, leveraging structured data models, such as taxonomies and ontologies, and ensuring data is interoperable across systems
3+ years of experience in developing and implementing solutions using APIs and SDKs
3+ years of experience in structuring and normalizing data, including in complex operational settings or workflows requiring machine-level compatibility
Ability to collaborate with mission stakeholders, technical developers, and operational users to ensure effective solutions
Ability to summarize findings and explain technical concepts clearly to both technical and non-technical stakeholders
Ability to learn and integrate new tools or resources as needed
Ability to be detail-oriented, self-driven, and work independently while meeting deadlines and objectives
Top Secret clearance
Bachelor’s degree in Data Science, Information Science, Computer Science, or Engineering

Nice To Haves

Experience developing semantic models for machine-to-machine interoperability, taxonomies, or data standardization efforts
Experience with semantic web technologies, such as RDF, OWL, JSON-LD, SKOS, and SHACL
Experience with cloud platforms, such as AWS, and working in agile environments using tools, such as JIRA or Confluence
Experience collaborating with cross-functional teams in high-priority, mission-driven settings
Knowledge of data processing workflows in operational ISR environments
Knowledge of geospatial data formats and concepts, such as GeoJSON or WKT, knowledge graphs, and ISR-specific data flows used in specialized geospatial environments, tools and software
Knowledge of IC-compliant frameworks and requirements for data handling
Knowledge of event-driven data design patterns and streaming technologies or workflows offsets to support integration workflows
Possession of excellent written and verbal communication skills
Master’s degree in Data Science, Computer Science, Engineering, or a related field

Responsibilities

Develop and implement data interoperability solutions to enable seamless interaction and usability of data across systems while adhering to DoW, AF, IC governance and compliance standards.
Conduct exploratory data analysis (EDA) and apply data science techniques, such as anomaly detection, to analyze and extract actionable insights from various datasets.
Design, build, and operationalize structured data models, taxonomies, and ontologies that comply with defined standards and mission requirements.
Translate unstructured and semi-structured data into actionable, normalized, and interoperable formats to improve operational and analytical workflows.
Create and implement IC-compliant taxonomy and ontology frameworks for organizing and classifying mission data.
Act as a bridge between technical developers and operators to ensure workflows and solutions meet mission objectives.
Write and refine data structuring requirements, providing expertise to improve codification and standardization efforts.
Represent organizational priorities in interactions with stakeholders while effectively communicating challenges, initiatives, and potential solutions to leadership.