Data Scientist with less than a year in Machine Learning, NLP, and Data Analytics.
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Data Scientist with a strong technical foundation in Machine Learning, NLP, and Data Analytics. Passionate about leveraging AI to solve local humanitarian challenges. Proven track record of building predictive models for food security (using WFP data) and disaster response systems. Seeking to apply data-driven insights to enhance humanitarian organizations' operational efficiency and aid distribution strategies.
Institute of Management Sciences, Peshawar
Bs · Data Science
August 1, 2022 – June 30, 2026
MandiMatrics: Pakistan Food Price Forecasting
June 1, 2025 – June 1, 2026
Built a time-series forecasting model using historical data from the World Food Programme (WFP). Utilized Python (Pandas, NumPy) for rigorous data cleaning and EDA to handle missing values and inconsistencies. Developed an interactive front-end using Streamlit to visualize district-level vulnerability trends dynamically. Enables humanitarian organizations to move from reactive aid to proactive planning by predicting which districts in Pakistan will face food insecurity before a crisis hits.
CrisisResponse AI: Intelligent Disaster Relief Pipeline
June 1, 2025 – June 1, 2026
Engineered an End-to-End Natural Language Processing (NLP) pipeline. Implemented text preprocessing (tokenization, stop-word removal) and trained a classification model to categorize unstructured social media text into actionable classes (e.g., "Shelter Needed," "Medical Emergency," "Safe"). Automates the filtering of thousands of incoming SOS messages during disasters, solving the problem of information overload and significantly reducing the response time for rescue teams.
CropDoc (Final Year Project)
June 1, 2025 – June 1, 2026
Developing a Computer Vision system using Deep Learning (Convolutional Neural Networks). The model is trained on image datasets of local crops to identify visual patterns of disease at early stages. Addresses the lack of agricultural expertise in remote rural areas by giving farmers an instant, AI-powered diagnosis tool to prevent crop failure and ensure food stability.
Intro to NLP for AI
365 Data Science
June 1, 2026 – Present
SQL
365 Data Science
June 1, 2026 – Present
Intro to AI
365 Data Science
June 1, 2026 – Present
Data Analytics
Change Mechanics Pvt Ltd
June 1, 2026 – Present
Statistics
365 Data Science
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects are diverse, covering NLP for disaster relief, time-series forecasting for food security, and computer vision for agriculture. This breadth of application, particularly in humanitarian contexts, suggests a strong alignment with roles that value social impact and innovative problem-solving. The target role 'Data Scientist' aligns well with the candidate's academic background and project experience. The academic nature of all projects, however, means there is no direct evidence of experience in a corporate or team-based professional environment, which could be a factor in cultural fit for certain organizations. The certifications from '365 Data Science' indicate a proactive approach to learning and skill development.
Soft Skills & Operational Fit
The candidate demonstrates a strong problem-solving attitude and a clear passion for leveraging AI to address humanitarian challenges. Their project descriptions highlight an ability to identify real-world problems and propose data-driven solutions. The focus on end-to-end project development suggests a capacity for independent work and a practical, results-oriented approach. However, without completed psychometric or English tests, it's difficult to assess logical reasoning, work attitude, stress handling, or team collaboration directly. The academic nature of all projects means real-world operational fit in a corporate or fast-paced environment is yet to be proven.