Senior Data Scientist
ANALYTICA
We are seeking an experienced Senior Data Scientist to develop and validate interpretable analytical signals for spending, concentration, duplication, and policy alignment for a Federal data analytics and AI modernization initiative.
The team will deliver a secure, scalable platform that integrates structured and unstructured data, provides data visualization and traceable AI-assisted analytics, and gives examiners centralized tools for search, review, monitoring, and decision support. The platform will support professional judgment and will not replace authoritative agency financial or grants-management systems or execute financial transactions.
Key Technical Responsibilities
- Design, develop, and maintain data pipelines and ETL/ELT workflows supporting machine learning, NLP, retrieval, and advanced analytics.
- Prepare, transform, curate, and validate structured and unstructured grants and financial data for AI/ML applications.
- Perform feature engineering, document processing, chunking, embeddings generation, and dataset preparation for AI-assisted analytics and retrieval workflows.
- Develop reproducible data transformations and workflows using Python, SQL, and applicable data engineering technologies .
- Implement and maintain data quality, validation, provenance, lineage, versioning, metadata, and source traceability throughout the data lifecycle.
- Prepare and integrate data for search, retrieval-augmented generation (RAG), visualization, analytics, and AI-assisted decision support .
- Troubleshoot data pipeline, transformation, integration, and data-quality issues across development and testing environments.
- Collaborate with multidisciplinary data engineering, data science, software engineering, and AI/ML teams during iterative development and testing.
- Develop technical documentation covering data architecture, pipelines, transformations, schemas, features, embeddings, dependencies, and operational procedures .
- Support deployment and operation of data engineering capabilities within secure Federal, on-premises, cloud, or hybrid environments .
- Ensure data engineering solutions comply with Federal security, privacy, accessibility, records-management, data-ownership, and governance requirements .
Required Technical Qualifications
- Demonstrated experience building, integrating, and operating data pipelines for machine learning, NLP, information retrieval, or advanced analytics.
- Hands-on experience with feature engineering, document processing, embeddings, curated datasets, data transformation, and reproducible data workflows .
- Strong proficiency in Python and SQL for data engineering, data transformation, automation, and model-support workflows.
- Experience working with structured and unstructured data and preparing data for AI/ML or analytics applications.
- Experience implementing data quality controls, data validation, provenance, metadata, versioning, lineage, and source traceability for AI/ML or data-intensive systems.
- Experience troubleshooting and optimizing data pipelines, integrations, transformations, and data-processing workflows .
- Ability to develop clear technical documentation covering data pipelines, schemas, transformations, dependencies, and operational processes .
- Strong technical communication, problem-solving, and cross-functional collaboration skills.
- U.S. citizenship and ability to obtain and maintain Top Secret eligibility , as required for contractor personnel supporting the effort.
- Active Top Secret clearance highly preferred.
Preferred Technical Qualifications
- Experience with Federal financial, grants, budget, payment, award oversight, or financial reporting data .
- Experience delivering solutions in secure Federal, on-premises, cloud, or hybrid environments .
- Experience with Linux .
- Experience with PostgreSQL and/or Microsoft SQL Server .
- Experience with Java and/or .NET .
- Familiarity with Jenkins and CI/CD pipelines .
- Experience with self-hosted Azure DevOps .
- Experience with Kubernetes and/or Rancher .
- Familiarity with open-source AI/ML models .
- Experience with RAG, vector databases/search, semantic search, or embeddings pipelines .
- Familiarity with Federal data governance, security, privacy, accessibility, and records-management requirements .
Analytica LLC is an Equal Opportunity Employer. We are committed to providing equal employment opportunities to all individuals, regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or any other characteristic protected by applicable federal, state, or local law. As a federal contractor, we comply with the Vietnam Era Veterans' Readjustment Assistance Act (VEVRAA) and take affirmative action to employ and advance in employment qualified protected veterans. We ensure that all employment decisions are based on merit, qualifications, and business needs. We prohibit discrimination and harassment of any kind. Analytica LLC also provides reasonable accommodations to applicants and employees with disabilities, in accordance with applicable law.
To enhance efficiency, fairness, and accuracy, Analytica may use AI-assisted tools to support certain aspects of our hiring process.
- Application Review: AI tools may help identify skills and experiences relevant to the role.
- Interview Support: AI-powered notetaking tools may be used during interviews to document discussions and summarize key points.
These tools are used to assist our team. All hiring decisions are made by Analytica recruiters and hiring managers.
By submitting an application, you acknowledge that AI-assisted tools may be used to support parts of the application and interview process.
When receiving email communication from Analytica, please ensure that the email domain is analytica.net to verify its authenticity.
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