Ministry of Municipalities & Housing • Knowledge Engineer

Lubna Bin Talib

لبنى عبدالعزيز طالب

Architecting Connected Knowledge Graphs & Executive AI.

Specialized in Knowledge Engineering, Semantic Graph Ontologies, Data Modeling, and Machine Learning. Transforming complex, multi-source enterprise information into structured knowledge graphs using Neo4j, Cypher, and RDF/OWL semantic standards.

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01. Perspective

Executive Profile

Bridging Unstructured Enterprise Information with Connected Intelligence

As a Knowledge Engineer with an academic foundation in Data Science & Analytics, my expertise lies in transforming fragmented multi-source information into structured knowledge models, taxonomies, and Knowledge Graphs.

By designing semantic ontologies in RDF/OWL and implementing enterprise graphs using Neo4j & Cypher, I establish the relational blueprint required for seamless data governance, automated knowledge discovery, and AI-ready semantic search systems.

Core Specialization
Knowledge Graphs & Semantic Ontology Engineering
Organization
Ministry of Municipalities and Housing (MOH)

Executive Contact

02. Graph Architecture

Knowledge Network Metrics & Schema

Select a core knowledge domain below to inspect connected node structures and operational metrics.

DOMAIN ONTOLOGY ARCHITECTURE

Ontology & Knowledge Schema Modeling

Structuring domain entities, attributes, and relationships into machine-readable ontology schemas using RDF, RDFS, and OWL standards for organizational knowledge discovery.

Connected Knowledge Nodes:
Enterprise Application:

Enables automated data validation, cross-departmental entity resolution, and semantic search integration.

Knowledge Network Overview Active Model
Graph Nodes
1,250+
Edge Relations
4,800+
Schema Standard
OWL / RDF
Engine Query
Neo4j Cypher
Status: Operational Graph Schema Connected
03. Career Track

Professional Experience

Current Role • Tamheer Program

Knowledge Engineer

Ministry of Municipalities and Housing (وزارة البلديات والإسكان)
07/2026 – Present
Riyadh, Saudi Arabia

Specialized in Knowledge Engineering through the AI & Data Co-op, expanding scope into Tamheer professional practice.

Transform unstructured information into organized, interconnected knowledge models through extraction, cleansing, and standardization.
Design domain ontologies, taxonomies, semantic models, and graph schemas by mapping entities, attributes, and relationships.
Build enterprise Knowledge Graphs using Neo4j and Cypher to enhance traceability, retrieval, and cross-domain data integration.
Contribute to AI-ready semantic knowledge solutions supporting semantic search, graph exploration, and executive insights.
Neo4j Cypher Query Ontology Design Semantic Web (RDF/OWL) Graph Schema Mapping
AI & Data Co-op Placement

Data Scientist

Ministry of Municipalities and Housing (وزارة البلديات والإسكان)
01/2026 – 07/2026
Riyadh, Saudi Arabia

Focused on Data Analytics, Business Intelligence dashboards, and Data Engineering workflows.

Analyzed operational and financial data; developed interactive Power BI dashboards for KPI tracking and operational insights.
Transformed and integrated multi-source data using Excel, Power Query, Python, and SQL for automated data preparation.
Contributed to early Knowledge Graph initiatives by identifying initial entity schemas and attribute relationships.
Power BI Power Query Python SQL Database ETL Workflows
04. Portfolio

Featured Projects

KNOWLEDGE ENGINEERING 02/2026 – Present

Connected Intelligence for Large-Scale Program

Structured and integrated information from diverse organizational sources into interconnected knowledge models. Contributed to entity mapping, ontology schemas, and Knowledge Graph implementation to enhance governance and discovery.

Neo4j Cypher Ontology Design
GRADUATION PROJECT • AI & NLP 08/2025 – 05/2026

Mohkem | AI Legal Warning System

Developed a hybrid AI decision-support system combining XGBoost predictive models, Arabic NLP via AraBERT, legal risk scoring analytics, and historical case retrieval for proactive risk evaluation.

XGBoost AraBERT Arabic NLP
DATA ENGINEERING 2025

StockFlow Analytics

Built an automated ELT pipeline to extract, transform, and prepare stock-market data for statistical analysis using Python scripts and SQL transformations.

Python SQL ELT Pipelines
POWER BI & HEALTH ANALYTICS 2025

Diabetes Patients Analysis

Constructed analytical dashboard suites in Power BI displaying patient risk factors, disease trends, and clinical health markers to facilitate medical decision support.

Power BI Power Query Health Trends
05. Capabilities

Technical Skill Matrix

Knowledge Engineering

  • Knowledge Graphs
  • Ontology Design
  • Semantic Modeling
  • Data Modeling
  • Taxonomies & SKOS

Tools & Standards

  • Neo4j & Cypher
  • RDF, RDFS, OWL
  • SPARQL & SHACL
  • Turtle (TTL)
  • Power BI & Power Query

ML & Arabic NLP

  • XGBoost Algorithms
  • TF-IDF Feature Extraction
  • AraBERT Language Models
  • Arabic Text Processing
  • Legal Risk Modeling

Languages & Pipeline

  • Python
  • SQL Database Querying
  • Cypher Querying
  • ELT / ETL Pipelines
  • Data Cleansing & Prep
06. Qualifications

Education & Certifications

Higher Education

B.Sc. in Data Science and Analytics
Princess Nourah bint Abdulrahman University
08/2022 – 06/2026 • Riyadh, Saudi Arabia
Leadership & Activities
Techminds Club Organiser

Professional Certifications

IBM Data Engineering
Microsoft Power BI Data Analyst
IBM Data Science
PrivacyOps Certification
Statistical Analysis Using R