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Umer M. Data Science, Machine Learning and Cloud Platforms

My name is Umer M. and I have over 2 years of experience in the tech industry. I specialize in the following technologies: Data Science, Data Analysis, Machine Learning, Python, GIS, etc.. I hold a degree in Master's degree, Bachelor's degree. Some of the notable projects I've worked on include: AI Assistant for Financial Organization, Floz: Cloud-based Flood Modeling Platform, ACWA Portal – Climate & Agriculture Intelligence System, Climate Risk Assessment Portal for Hazards, Exposure & Vulnerability, Automated AI based Boundary Detection, etc.. I am based in Lahore, Pakistan. I've successfully completed 8 projects while developing at Softaims.

I thrive on project diversity, possessing the adaptability to seamlessly transition between different technical stacks, industries, and team structures. This wide-ranging experience allows me to bring unique perspectives and proven solutions from one domain to another, significantly enhancing the problem-solving process.

I quickly become proficient in new technologies as required, focusing on delivering immediate, high-quality value. At Softaims, I leverage this adaptability to ensure project continuity and success, regardless of the evolving technical landscape.

My work philosophy centers on being a resilient and resourceful team member. I prioritize finding pragmatic, scalable solutions that not only meet the current needs but also provide a flexible foundation for future development and changes.

Main technologies

  • Data Science, Machine Learning and Cloud Platforms

    2 years

  • Data Science

    1 Year

  • Data Analysis

    1 Year

  • Machine Learning

    1 Year

Additional skills

Direct hire

Potentially possible

Previous Company

Farmdar

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Experience Highlights

AI Assistant for Financial Organization

Developed a secure, containerized Retrieval-Augmented Generation (RAG) system for an international audit firm. The assistant supported contextual querying across PDFs, Word files, and databases using

Floz: Cloud-based Flood Modeling Platform

Designed and deployed a real-time flood simulation backend using Python Flask, integrated with geospatial tools (GeoPandas, Rasterio), hydraulic models (HEC-RAS, SFINCS), and cloud infrastructure (AWS

ACWA Portal – Climate & Agriculture Intelligence System

Developed a cloud-enabled WebGIS platform for the Indus Basin, integrating real-time satellite (MODIS, Sentinel) and climate data (ERA5, CHIRPS) to support agricultural planning, water management, and

Climate Risk Assessment Portal for Hazards, Exposure & Vulnerability

Built a backend system for a geospatial portal that monitors climate-related hazards like floods, heatwaves, and droughts using satellite data, climate models, and exposure indicators. Developed autom

Automated AI based Boundary Detection

A pilot initiative to test whether a AI–based boundary detection system—powered by higher-resolution imagery and advanced segmentation—could deliver precise, smooth, latest field polygons with minimal

Education

  • Univeristy of Management and Technology

    Master's degree in Data Science

  • National University of Computer and Emerging Sciences

    Bachelor's degree in

Languages

  • English (Fluent)
  • Panjabi, Punjabi (Fluent)
  • Urdu (Native or Bilingual)