FANOOS HAIDER | Gravity Talent Portal

FANOOS HAIDER | Gravity Talent Portal

Projects

Modeling Forest-Trees Survival Rate Geospatial Technology

June 1, 2026 – Present

Analyzed forest-tree survival rates using geospatial technologies, focusing on the Billion Tree Tsunami Afforestation Project in Peshawar Division. Utilized remote sensing data and geospatial modeling to evaluate afforestation outcomes and their impact on environmental sustainability.

Mapping Forest Ecosystem Services | InVEST Model

June 1, 2026 – Present

Integrated remote sensing and GIS with the InVEST model to map forest ecosystem services, focusing on sediment retention in watersheds.

Web Scraping & News Data Pipeline

June 1, 2026 – Present

Developed a web scraping system to extract news data, followed by data cleaning and preprocessing. Stored structured data into databases for efficient querying and analysis. Automated the workflow for continuous data collection and storage.

3D Vertical GIS Projects – Imarat Group of Companies

June 1, 2026 – Present

Worked on 3D vertical mapping and digitization of high-rise building structures. Integrated floor-wise spatial data with attributes for accurate visualization. Created analysis-ready datasets for planning and decision-making.

Land Use Change Impact on Soil Erosion RUSLE Model

June 1, 2026 – Present

Assisted in research to study the impact of land use and cover changes on soil erosion rates in the Mangla Watershed. Applied the RUSLE model to estimate soil loss and identified critical areas needing intervention.

Monitoring Land Cover Change in Khushab GIS

June 1, 2026 – Present

Conducted a comprehensive analysis of land cover change over two decades in the Khushab District of Punjab. Utilized geospatial techniques to identify patterns and drivers of land cover transformation.

Fire Prediction Mapping in Margalla Hills

June 1, 2026 – Present

Developed geospatial mapping techniques for fire prediction in Margalla Hills using Google Earth Engine. Analyzed environmental parameters and historical fire data to predict high-risk zones.

Flood Area Extraction in E11 Islamabad

June 1, 2026 – Present

Mapped flood-prone areas in E11 Islamabad using Sentinel satellite data in Google Earth Engine. Provided actionable insights for flood mitigation and risk management.

Large-Scale Parcel Data Scraping (USA)

June 1, 2026 – Present

Scraped and processed parcel data across multiple US states, handling datasets at billion-scale. Converted API responses into structured formats (GeoJSON/Shapefiles) for GIS use. Optimized data extraction and storage for performance and scalability.

Mapping COVID-19 Cases with Web GIS

June 1, 2026 – Present

Designed and deployed an interactive GIS website to visualize the spatial distribution of COVID-19 cases. Integrated real-time datasets for tracking pandemic trends and patterns.

RS and GIS Applications Dashboard

June 1, 2026 – Present

Built an interactive dashboard to streamline the analysis of remote sensing and GIS applications. Integrated Google Earth Engine for real-time data processing and visualization.

Data Visualization via PostgreSQL on Web

June 1, 2026 – Present

Designed data visualization workflows using PostgreSQL/PostGIS as backend. Displayed spatial and non-spatial data on web platforms for user interaction. Enabled efficient querying and real-time visualization of large datasets.

Key Strengths

Extensive experience in geospatial data processing, database management, and remote sensing, directly aligning with the target role of Geospatial Data Scientist.
Proficiency in Python, SQL, PostGIS, and various GIS software (ArcGIS Pro, QGIS, Google Earth Engine), which are critical for the role.
Demonstrated ability to design and implement scalable geospatial data pipelines and automate spatial data processing tasks, as evidenced by professional experience.
Strong academic background with a Master's and Bachelor's in Remote Sensing and GIS/Geo-Informatics, indicating a solid theoretical foundation.
Experience with large-scale data scraping and processing (e.g., billion-scale parcel data), showcasing ability to handle significant data volumes.
Practical application of geospatial modeling for environmental analysis, urban planning, and risk management (e.g., forest survival rates, fire prediction, flood mapping).

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's project diversity, ranging from environmental sustainability (forest survival, soil erosion, land cover change) to urban planning (3D vertical GIS, flood mapping) and public health (COVID-19 mapping), indicates a broad interest and adaptability. The professional experience across multiple companies (Imart Group, Zoneomics, SpatialOX, SAWIE, LSWO) in various GIS-related roles demonstrates a willingness to engage with different organizational contexts. The academic background and continuous learning through certifications align well with a culture that values expertise and growth. The focus on data-driven solutions and automation suggests a fit for results-oriented environments.

Soft Skills & Operational Fit

The candidate's resume highlights a focus on automating workflows and improving efficiency, suggesting a proactive and problem-solving approach. The descriptions of collaborative optimization of spatial databases indicate teamwork and communication skills. The academic projects demonstrate strong analytical thinking and the ability to apply complex models to real-world problems. The candidate's interest in continuous learning of new GIS tools and coding in Python, along with researching tech trends, indicates a strong drive for self-improvement and staying current with industry advancements.