Title: Semantic/AI Data Architect
Location: Hybrid in Atlanta or Alpharetta, GA (2 days WFH)
Industry: Financial Services
Compensation: $60-$82/Hour (Contract-to-Hire)
We’re partnering with a leading financial services organization to find a Semantic/AI Data Architect. In this role, you will play a key part in aligning data architecture with enterprise strategies by leveraging taxonomy, ontology development, graph schema design, and semantic AI to enhance data processing, analysis, and governance. Your work will empower business teams by enabling data insights through advanced AI technologies while ensuring compliance with regulatory standards.
This role requires a strong balance of technical, compliance, and business acumen to drive innovation, improve efficiency, and maintain data reliability.
Key Responsibilities
1. Taxonomy and Ontology Development
- Collaborate with business teams to understand domain-specific terminology and concepts.
- Design, build, and maintain taxonomies and ontologies to capture relationships between entities and concepts.
- Improve search, knowledge management, and information retrieval through robust taxonomies.
2. Graph Schema Design and Implementation
- Develop and implement graph data models to represent complex entity relationships in the financial domain.
- Optimize graph database performance and scalability in collaboration with database administrators.
- Create queries and algorithms to derive actionable insights from graph data.
3. Semantic AI Integration
- Utilize AI technologies (e.g., NLP, ML) to enhance taxonomies and graph models.
- Develop semantic search, entity recognition, and relationship extraction algorithms.
- Improve the efficiency and accuracy of data analysis through semantic AI.
4. Data Governance and Compliance
- Ensure data models, taxonomies, and AI applications meet regulatory and industry standards.
- Develop and implement data governance policies and procedures.
- Collaborate with legal and compliance teams to ensure ethical and responsible data use.
- Align data architecture with business goals, supporting data acquisition, storage, analysis, and delivery.
Skills & Qualifications
Required Skills
- Expertise in semantic web technologies, taxonomies, ontologies, and graph databases.
- Proficiency in graph query languages (SPARQL, Cypher).
- Experience with data modeling techniques and tools.
- Strong knowledge of AI/ML solutions (e.g., NLP).
- Proficiency in programming languages like Python and Java.
- Familiarity with data visualization and reporting tools.
- Strong understanding of financial services industry data and compliance requirements.
Soft Skills
- Analytical and problem-solving skills with attention to detail.
- Exceptional communication skills to translate technical concepts into business terms.
- Collaborative mindset and ability to work with cross-functional teams.
- Business insight to understand the impact of data on decision-making processes.
Education & Experience
- Bachelor’s degree in a STEM field; Master’s degree strongly preferred.
- 5-7 years of data analysis and modeling experience.
- Technical certifications (e.g., cloud technologies) are a plus.
Preferred Skills
- Experience designing and implementing relational and non-relational data models in platforms like GCP, Oracle, or Microsoft.
- Familiarity with risk management principles and regulatory standards in financial services.
- Ability to model complex data entities and relationships for business and technical use cases.
