Data Scientist

9th Way Insignia is seeking a Data Scientist to support a government customer in Washington, DC. The Data Scientist will support enterprise data modernization, advanced analytics, reporting, automation, and decision-support initiatives across multiple business lines. This position aligns to the Engineer 3 professional level within 9th Way Insignia’s career families and is expected to operate as a senior technical resource with strong analytical depth, architectural awareness, and the ability to support production delivery with minimal ramp-up time.

Professional Level Information

An Engineer, 3 typically plans and directs research or development work on complex projects, along with engaging various parties in design and development. Costs and recommendations of new components may also involve part of the job scope. Performs multiple engineering-related tasks in various assignments within the project and firm. An Engineer, 3 oversees the design, development, implementation, and analysis of technical products and systems. An Engineer, 3 has broad knowledge of engineering procedures and assists in the resolution of complex problems. An Engineer, 3 has strong technical skills and background, a knack for learning new technologies, and a blend of good problem-solving and innovation needed to resolve a wide variety of technical production challenges.

Functional Job (LCAT) Information

The Data Scientist is responsible for analyzing and architecting data solutions that support enterprise reporting, analytics, operational decision-making, and future business line priorities. This role serves as a senior technical contributor focused on understanding complex datasets, identifying trends, gaps, anomalies, and structural risks, and designing data architectures and analytical approaches that improve the quality, accessibility, and usability of enterprise information.

The Data Scientist works closely with ETL Developers, Power BI Developers, Data Analysts, Power Apps Developers, Technical Project Managers, testers, technical writers, and Government stakeholders to assess data sources, define business and technical data requirements, evaluate impacts across systems, and guide the implementation of sustainable enterprise solutions. This role also contributes to technical planning, ROM development, task breakdowns, documentation, and identification of risks, dependencies, and opportunities for efficiency in support of more mature and predictable delivery.

Responsibilities

• Be available on Government site in Washington, DC during normal hours of operation.
• Analyze complex business processes, operational requirements, and enterprise datasets to identify opportunities for improved reporting, analytics, automation, and decision support.
• Assess existing and proposed data sources to evaluate structure, quality, completeness, relationships, lineage, and suitability for enterprise reporting and analytical use.
• Design and maintain conceptual, logical, and physical data models supporting enterprise data warehouse, reporting, and analytics initiatives.
• Develop enterprise data architecture recommendations that align business objectives with scalable, maintainable, and governed data solutions.
• Translate business requirements into technical specifications, data definitions, integration approaches, and implementation-ready solution designs.
• Collaborate with ETL Developers, Database Engineers, Data Analysts, and reporting teams to define source-to-target mappings, business rules, transformation logic, and data validation strategies.
• Conduct data profiling, root-cause analysis, and impact assessments to identify data quality issues, inconsistencies, gaps, and reporting risks.
• Support enterprise reporting modernization initiatives, including migration of legacy reporting solutions and development of future-state analytical capabilities.
• Evaluate existing reporting, analytics, and integration solutions and identify opportunities for optimization, standardization, modernization, and reuse.
• Support requirements analysis, backlog refinement, sprint planning, sprint demonstrations, and agile delivery activities.
• Contribute to minimum viable product planning and incremental enhancement of enterprise data and analytical capabilities.
• Provide technical recommendations regarding solution architecture, task sequencing, ROM estimates, risks, dependencies, alternatives, and opportunities for improved efficiency or reuse.
• Develop and maintain architecture documentation, data dictionaries, data flow diagrams, source-to-target mappings, logical data models, operational procedures, and technical design artifacts.
• Support testing, validation, and user acceptance activities to ensure solutions meet business and technical requirements.
• Promote standard approaches to delivery, data governance, documentation, and repeatable practices supporting process maturity and predictable outcomes.
• Support cloud migration, modernization, and architectural enhancement initiatives as required.
• Mentor less senior team members and support the overall quality and maintainability of technical deliverables.
• Support multiple business lines and enterprise priorities as required.
• Other responsibilities as assigned.

Requirements

• Master’s degree in Computer Science, Information Systems, Data Science, Data Analytics, Mathematics, Statistics, Engineering, or other technical discipline. Additional relevant experience may be substituted for a degree consistent with contract requirements.
• Minimum 5 years of relevant experience in data architecture, data analysis, data science, enterprise analytics, data warehousing, or related technical delivery roles. Ten (10) additional years of experience may be substituted in lieu of a degree.
• Demonstrated experience analyzing large datasets and identifying trends, gaps, anomalies, structural risks, and data integrity issues.
• Experience designing or supporting conceptual, logical, and physical data models in enterprise environments.
• Experience translating ambiguous business needs into structured data logic, technical requirements, and implementable architectural approaches.
• Experience validating business rule implementation and providing corrective guidance to technical delivery teams.
• Experience with SQL, relational data structures, data integration concepts, and enterprise reporting or analytics environments.
• Experience supporting enterprise data warehouse, business intelligence, analytics, or decision-support initiatives.
• Experience supporting agile or iterative delivery efforts with backlog-driven work, sprint-based execution, and incremental releases.
• Experience preparing and maintaining technical documentation supporting architecture, operations, continuity, and knowledge transfer.
• Ability to operate effectively in an enterprise production environment with minimal ramp-up time.
• Must be authorized to work for any employer in the U.S.
• Must be able to obtain and maintain the required security clearance.

Preferred / Desired

• Experience supporting Federal Government customers in enterprise data warehouse, reporting, analytics, or decision-support environments.
• Experience supporting Veterans Affairs (VA), CMS, SSA, SEC, or other large federal data environments.
• Experience supporting enterprise data warehouse architectures, dimensional modeling, data marts, metadata management, and reporting modernization initiatives.
• Experience supporting migration of legacy reporting platforms to modern analytics and visualization platforms.
• Experience working with Power BI, Tableau, OBIEE, Cognos, Business Objects, MicroStrategy, or similar enterprise BI platforms.
• Experience working closely with ETL, reporting, database, and application development teams in governed production environments.
• Experience contributing to ROM development, effort estimation inputs, and documentation of risks, dependencies, and alternatives.
• Experience supporting cloud migration, modernization, or enterprise architecture initiatives.
• Experience working in environments emphasizing documentation, process maturity, repeatability, governance, and disciplined delivery practices.