Sr Data Scientist

Innovative Computer Solutions Group, Inc; Reston (VA); Hybrid; USD 130,000 - 190,000; Full time

Benefits offered by this job

Flexible work options

Job summary

Innovative Computer Solutions Group, Inc. is seeking a Senior Data Scientist to design and implement enterprise tagging and metadata governance across distributed data environments.

You will translate business requirements into metadata schemas, tagging capabilities, and semantic models while collaborating with data, security, and governance teams. The role emphasizes evolution of ontologies, taxonomies, and knowledge graphs, with a focus on secure data movement and DoD/IC-aligned practices.

Qualifications

• Strong understanding of enterprise data tagging and metadata management principles.
• Experience defining minimum metadata and tagging requirements across enterprise environments.
• Knowledge of AI/ML-assisted tagging approaches and metadata extraction.
• Experience with metadata schema development, mapping, and standards implementation.
• Familiarity with RDF, OWL, SKOS, JSON-LD and related semantic technologies.
• Experience enabling tagging services within data lakes, catalogs, and pipelines.
• Experience with data governance, lineage, and security metadata.

Responsibilities

• Translate mission requirements into technical metadata and tagging capabilities.
• Define metadata requirements and develop semantic models.
• Evaluate tagging approaches including AI/ML-assisted methods.
• Integrate enterprise tagging with data lakes, catalogs, and pipelines.
• Govern ontologies, taxonomies, and controlled vocabularies across domains.
• Ensure metadata persists across security boundaries and data movements.

Skills

Data tagging

Metadata management

Ontologies

Taxonomies

Semantic data

Data governance

ABAC

Policy enforcement

Metadata schemas

Knowledge graphs

APIs integration

Data catalogs

Tools

RDF/OWL/JSON-LD

SQL/ETL

Job description

This position is mostly remote but will require occasional visits to the client site in Reston, VA. Active TS/SCI clearance with the ability to pass a polygraphy.

The Senior Data Scientist will support the design, implementation, and integration of an enterprise-scale data tagging and metadata management capability across complex, distributed data environments. The project will establish standardized metadata, tagging, taxonomies, ontologies, and governance processes to improve data discovery, interoperability, quality, access control, sharing, and dissemination.

The role will work across data science, data engineering, enterprise architecture, cybersecurity, data governance, and mission stakeholders to translate business and mission requirements into technical metadata and tagging capabilities. Responsibilities will include defining minimum metadata requirements, developing metadata schemas and semantic models, evaluating automated and AI/ML-assisted tagging approaches, and integrating enterprise tagging services with data lakes, data platforms, repositories, catalogs, pipelines, and consuming applications.

The Senior Data Scientist will also contribute to the development and governance of enterprise ontologies, taxonomies, controlled vocabularies, and knowledge graph capabilities. The position will evaluate data flows and architectures to ensure metadata and security attributes persist, propagate, and remain enforceable as data moves across systems and security boundaries.

Required Skills and Experience

Data Tagging & Metadata

• Strong understanding of enterprise data tagging and metadata management principles, architectures, and technologies.
• Experience defining and implementing minimum metadata and tagging requirements across enterprise data environments.
• Knowledge of automated, rules-based, manual, and AI/ML-assisted tagging approaches.
• Experience with metadata extraction, enrichment, classification, validation, and normalization.
• Understanding of tag persistence, inheritance, propagation, and synchronization as data moves between systems.
• Experience with metadata schema development, mapping, crosswalks, and standards implementation.
• Knowledge of metadata lineage, provenance, versioning, quality, and lifecycle management.
• Experience integrating tagging capabilities with enterprise metadata repositories, data catalogs, and other metadata services.

Ontologies, Taxonomies & Semantic Data

• Strong understanding of ontologies, taxonomies, controlled vocabularies, and semantic data models.
• Experience developing, implementing, or managing enterprise and domain-specific ontologies.
• Ability to map relationships between disparate schemas, vocabularies, taxonomies, and ontologies.
• Understanding of ontology governance, versioning, extensibility, and lifecycle management.
• Familiarity with semantic technologies and standards such as RDF, OWL, SKOS, JSON-LD, or comparable technologies.
• Knowledge of knowledge graphs and semantic search/discovery is highly desirable.

Data Governance

• Strong understanding of enterprise data governance, including data ownership, stewardship, authoritative sources, data quality, metadata standards, and lifecycle management.
• Experience translating governance policies into enforceable technical requirements.
• Knowledge of metadata governance, schema governance, ontology governance, and change-control processes.
• Ability to establish and enforce minimum required metadata for data ingestion, discovery, access, sharing, and dissemination.
• Understanding of data classification, handling, sharing, retention, and dissemination requirements.
• Experience operating within DoD and/or Intelligence Community data governance environments strongly preferred.
• Familiarity with applicable IC Directives (ICDs), IC standards, and DoD/IC data and information-sharing requirements, including requirements associated with metadata, access, handling, and dissemination.

Enterprise Tagging Services

• Understanding of enterprise tagging architectures and centralized/shared tagging services.
• Experience defining or implementing an Enterprise Tagging Service (ETS) and/or Minimum Viable Tagging Service (MVTS) capability.
• Ability to define enterprise tagging requirements, required metadata attributes, validation rules, and service interfaces.
• Understanding of how tagging services integrate with data ingestion pipelines, repositories, catalogs, search/discovery capabilities, and consuming applications.
• Experience designing or implementing APIs and services for creating, retrieving, updating, validating, and exchanging tags and metadata.
• Understanding of how metadata and tags can support discovery, access decisions, handling, and dissemination.

Enterprise Metadata Repository

• Experience with enterprise metadata repositories and/or data catalogs.
• Understanding of metadata registration, storage, discovery, retrieval, synchronization, and federation.
• Ability to integrate metadata repositories with multiple data platforms, tagging services, applications, and data pipelines.
• Experience managing relationships between business, technical, operational, security, and governance metadata.
• Understanding of authoritative metadata sources and mechanisms for resolving duplicate, incomplete, or conflicting metadata.

Data Architecture & Integration

• Strong understanding of modern enterprise data architectures, including data lakes, lakehouses, data fabrics, data meshes, catalogs, repositories, and distributed data environments.
• Experience integrating metadata and tagging capabilities through APIs, ETL/ELT pipelines, event-driven architectures, and enterprise services.
• Ability to assess whether technical solutions can meet functional, integration, performance, scalability, security, and governance requirements.
• Experience identifying integration dependencies, architectural constraints, interoperability issues, and technical gaps.
• Ability to distinguish between native capability, configuration, customization, third-party dependencies, and custom development.

Security & Data-Centric Access

• Understanding of data-centric security and Zero Trust principles.
• Familiarity with Attribute-Based Access Control (ABAC) and the use of metadata attributes in policy decisions.
• Understanding of Policy Decision Point (PDP) and Policy Enforcement Point (PEP) concepts.
• Knowledge of security metadata, classification, releasability, handling, and dissemination controls.
• Understanding of metadata persistence and policy enforcement as data moves across systems and security boundaries.
• Familiarity with cross-domain and multi-domain data-sharing environments is highly desirable.

Technical & Analytical Skills

• Translate mission and business needs into detailed data, metadata, tagging, ontology, and governance requirements.
• Evaluate technical capabilities against enterprise requirements and identify functional or architectural gaps.
• Develop detailed technical questions and use cases to validate whether a capability performs as required.
• Analyze complex data flows and determine where, when, how, and by whom metadata should be created, applied, validated, updated, and consumed.
• Work across data science, data engineering, architecture, cybersecurity, governance, and mission teams.
• Communicate complex metadata and data architecture concepts to both technical and non-technical stakeholders.
• Develop technical documentation, data models, metadata models, interface requirements, governance artifacts, and architecture diagrams.
• Provide technical leadership during implementation, integration, testing, deployment, and continuous improvement of enterprise tagging capabilities.

Preferred Qualifications

• 8+ years of experience in data science, data engineering, data architecture, metadata management, semantic technologies, or data governance.
• Bachelor's or Master's degree in Data Science, Computer Science, Information Systems, Data Engineering, or a related technical discipline.
• Demonstrated experience with enterprise-scale metadata or data management implementations.
• Experience supporting DoD, Intelligence Community, or other highly regulated government data environments.
• Experience working with commercial data catalog, metadata management, semantic/ontology, or enterprise data platforms.
• Strong technical facilitation, requirements analysis, and vendor engagement skills.
• Active TS/SCI clearance required based on program needs.

Core Competencies

Enterprise Data Tagging | Metadata Management | Metadata Standards | Ontologies | Taxonomies | Semantic Data | Data Governance | Enterprise Metadata Repositories | Data Catalogs | Data Lineage & Provenance | Data Architecture | API Integration | Data-Centric Security | ABAC | Zero Trust | DoD/IC Data Environments

Flexible work from home options available.