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Data Scientist
SignificancePosted 10/21/2026full-timeRemote • United StatesMid-LevelSenior💰 $115,000 - $125,000 per yearWebsite
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in database architecture, SQL, and data governance while effectively managing large-scale data models and automated workflows. Proficient in Python or R for data engineering and analytics, with strong communication skills to bridge technical and non-technical stakeholders.
Highest-signal resume keywords
Database ArchitectureSQL ProficiencyData Governance ExpertisePython or R ProficiencyETL Pipeline Experience
Tech Stack
Tools & technologiesAbout the role
Key responsibilities & impact- Develop, maintain, and optimize databases and structured data systems to support enterprise information needs
- Create and manage data models, schemas, dictionaries, and standards
- Conduct data quality checks, validation routines, and governance processes
- Design and implement data ingestion, transformation, and lifecycle management processes
- Perform advanced analytical modeling, including scenario analysis, forecasting, and risk assessment
- Develop tools, scripts, and automated workflows to streamline data processing and improve system performance
- Collaborate with cross-functional teams to translate data requirements into technical solutions
- Evaluate data-related capabilities, recommend improvements, and support integration activities
- Provide subject matter expertise on enterprise data management best practices and emerging technologies
Requirements
What you’ll need- Active Secret clearance required
- Strong proficiency in database architecture, SQL, and structured data environments
- Experience developing and maintaining large-scale data models and metadata frameworks
- Expertise in data governance, data quality assurance, and standardized data practices
- Proficiency in Python or R for data engineering, analytics, and scientific computing
- Experience with ETL pipelines, data validation tools, and automated data workflows
- Ability to analyze complex datasets and develop analytical models to support organizational strategy
- Excellent communication skills, with the ability to convey technical concepts to non-technical stakeholders
- Four years of experience in Navy data systems desired
- Background in infrastructure, engineering, or large enterprise operational environments desired
- Familiarity with data standardization initiatives and enterprise data architectures desired
- Knowledge of cloud-based data platforms, distributed data systems, or API-driven architectures desired
- Experience mentoring junior data staff or contributing to enterprise data strategy desired
- Experience in Navy Systems such as eProjects, ieFACMAN, and iNFADS desired
Benefits
Comp & perks- Comprehensive and generous benefits package
- E-Verify Employer
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Database ArchitectureSQLData ModelingData GovernanceData Quality AssuranceETL PipelinesAnalytical ModelingData ValidationAutomated WorkflowsData Transformation
Soft Skills
Excellent Communication Skills
Tools & Technologies
Data Validation ToolsCloud-Based Data PlatformsDistributed Data SystemsAPI-Driven Architectures
Certifications & Qualifications
Active Secret Clearance
Industry Keywords
Navy Data SystemsEnterprise Data ManagementData Standardization InitiativesInfrastructure EngineeringLarge Enterprise Operational Environments