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M.Abdullah
@abdullah_hash
Data Scientist, AI Python Developer and GIS Specialist
Pakistan
Inglese
Chi sono
Data Scientist and AI Python Developer and GIS Expert with expertise in data engineering, geospatial analytics, and AI solutions. Experienced in building scalable ETL pipelines, spatial databases (PostgreSQL/PostGIS), and machine learning models. Skilled in web scraping, LLM-based data extraction, and backend API development using Python, FastAPI, and Flask. I help organizations automate data workflows, process complex datasets, and build dashboards and analytics systems that support data-driven decision making.
Competenze
M.Abdullah
offline •
Tempo di risposta medio: 1 ora
Consulta i miei servizi
Machine learning
I will build ai and machine learning solutions in python
Dashboard dati
I will create data visualizations in python, r, and power bi
Esperienza lavorativa
Senior Data Science
Zoneomics • Full time
Jul 2023 - Present • 2 yrs 10 mos
Implementing and Handling Multiple Project some includes: • FADIP Pipeline Development: Designed a Python-based pipeline to process raw geometries, PLUs, and control data, transforming and storing them in PostgreSQL, boosting data flow efficiency and accuracy. • Designed and documented a comprehensive suite of Elasticsearch Mustache-based search templates to power parcel - and zoning-level analytics across different indices. Implemented dynamic filters, aggregation logic, and performance-optimized query flows supporting city, FLUM, PLU, and ZIP-based data retrieval — forming the backbone for internal BI dashboards and map-based search UIs. • Developed a FastAPI-based Zoning Extractor microservice integrating PostgreSQL, Jinja2 UI, and OpenAI LLMs to automate extraction of zoning controls and land-use data from municipal documents. • AI Zoning Agent Development: Built a Python-based AI agent using LangGraph to automate zoning research workflows, including web scraping, email extraction, and response classification, significantly reducing manual effort. • Parking Data Extraction Project: Automated extraction of parking-related data from municipal documents using web scraping, machine learning models, and LLMs. • Permits Data Extraction Project: Extracted and processed permit data from ArcGIS and city websites, structuring it with LLMs and indexing in Elasticsearch for quick retrieval. • IMDAD System Development: Built a Python-based backend system that automatically detects changes in city geometries by fetching data in real time from various ArcGIS sources and notifies updates, ensuring accurate and timely data management in PostgreSQL.
