Data Scientist SME Taxonomy & Data Migration Consultant

Position Overview

We are seeking a senior Data Scientist SME with deep expertise in data architecture and taxonomy to lead the design of the target data architecture for a USFWS modernization initiative. This role will define the canonical taxonomy, reconciliation logic, data-quality standards, and technical specifications that govern the migration of legacy permitting and wildlife-trade data into PostgreSQL and Amazon DynamoDB.

Key Responsibilities

• Define the target-state data architecture for migrating USFWS legacy permitting and wildlife-trade data to PostgreSQL (relational) and DynamoDB (NoSQL).
• Design and maintain a canonical taxonomy, including species nomenclature and reference data alignment.
• Develop reconciliation logic to resolve conflicting, duplicate, or outdated records across legacy sources.
• Establish measurable data-quality standards, controls, and lineage tracking.
• Design exception-handling and adjudication workflows for records that fail validation or reconciliation.
• Produce implementation-ready, machine-readable technical specifications (e.g., JSON Schema, OpenAPI, event schemas) for development teams.
• Guide normalization and performance-aware schema design in PostgreSQL, and access-pattern-driven design in DynamoDB.
• Collaborate with engineering, program, and security stakeholders to ensure alignment with federal compliance requirements.

Required Qualifications

• Expert-level experience in data architecture, data modeling, master/reference data management, taxonomy reconciliation, or complex data-quality initiatives.
• Advanced SQL and PostgreSQL skills, including normalization and performance-aware schema design.
• Hands-on experience with NoSQL/document databases and access-pattern-driven design (DynamoDB strongly preferred).
• Proven experience defining measurable data-quality controls, data lineage, reconciliation, and exception/adjudication workflows.
• Demonstrated ability to produce implementation-ready, machine-readable technical specifications.

Preferred Qualifications

• Master's degree (or equivalent experience) in Data Science, Computer Science, Information Systems, Bioinformatics, Taxonomy, or a related field.
• Experience with biological taxonomy, biodiversity data, species nomenclature, CITES or LEMIS data, or authoritative taxonomy services (e.g., ITIS, GBIF).
• AWS data architecture experience, including RDS/Aurora PostgreSQL, DynamoDB, S3, and orchestration services (e.g., Step Functions, Glue, Airflow).

• Experience with OpenAPI, event schemas, JSON Schema, data catalogs, knowledge graphs, or metadata-management platforms.

• Familiarity with FISMA, NIST SP 800-53, FedRAMP, Privacy Act, Zero Trust, and federal records management requirements.