Senior Data Scientist

We are a federal IT company on a mission to make customer experience (CX) the center of every government solution. Technology is our Passion. People are our Purpose. We know tech, but we love people. NuAxis is home to thinkers and feelers; engineers and artists. We work hard and support each other along the way. Teamwork is more than just a buzzword for us, it’s a state of mind.

We believe happy employees do amazing work, so join our team NOW! We are currently seeking a talented and motivated Senior Data Scientist for a Full-Time position. Role Summary The Senior Data Engineer / Data Scientist will serve as a hands-on data engineering and analytics specialist responsible for modernizing decades of structured, semi-structured, and document-based data for our client. The role will focus on building secure, traceable, scalable, and AI-ready data assets through robust data pipelines, document processing, data quality, lineage, and governance practices.

The ideal candidate will have strong experience designing modern data platforms and ETL/ELT pipelines in AWS environments, along with hands-on expertise in Python, SQL, PostgreSQL, DynamoDB, document processing, OCR, and data-quality management.

Key Responsibilities Design, develop, and maintain Bronze, Silver, and Gold layer data pipelines using modern medallion and lakehouse architecture principles. Ingest and process legacy structured, semi-structured, and unstructured data from multiple sources. Develop scalable, reproducible, and idempotent ETL/ELT pipelines for large and complex datasets. Implement data transformation, normalization, validation, cleansing, and quarantine processes. Maintain comprehensive record-level data lineage from source systems through downstream datasets.

Capture and manage metadata required to support data discovery, traceability, governance, and auditing. Design and implement relational data structures using PostgreSQL. Develop appropriate data models and access patterns for DynamoDB and document-oriented data. Support AWS-based data ingestion, processing, storage, and analytics workflows. Process scanned permits, certificates, applications, and other document-based records. Implement OCR and document-intelligence solutions to extract structured information from scanned documents.

Track extracted values back to the originating document, page, and relevant region or location. Implement field-level confidence scores and validation mechanisms for extracted information. Develop workflows to route low-confidence or potentially inaccurate extractions for human review. Implement processes for identifying, masking, protecting, and appropriately controlling access to PII and sensitive information. Develop data-quality checks, validation rules, exception handling, and quarantine mechanisms.

Identify and resolve data inconsistencies, missing values, duplicates, formatting issues, and other legacy-data quality problems. Develop data-quality scorecards and metrics to monitor completeness, accuracy, consistency, and reliability. Ensure pipelines and data-processing workflows are secure, auditable, maintainable, and well documented. Develop technical documentation covering pipeline architecture, data mappings, transformations, lineage, validation rules, and operational procedures. Collaborate with data scientists, data analysts, engineers, security teams, and business stakeholders to support data modernization initiatives.

Support the development of trusted, standardized, and AI-ready datasets for downstream analytics and machine-learning applications.

Required Qualifications 7–10+ years of experience in data engineering, data science, data analytics, or a related field. Advanced programming experience with Python and…