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Schedule Interview NowMy name is ALI ARMAGHAN A. and I have over 12 years of experience in the tech industry. I specialize in the following technologies: Python, pandas, NumPy, Data Science, Machine Learning, etc.. I hold a degree in Master of Science (MS), Bachelor of Computer Science (BCompSc). Some of the notable projects I've worked on include: Voice Chatbot Development and Deployment using LLMs, Audio-to-Insights Extraction using Whisper ASR and ChatGPT, Credit Card Churn Prediction, Cotton Crop Classification using Sentinel-2 Data. I am based in Lahore, Pakistan. I've successfully completed 4 projects while developing at Softaims.
I specialize in architecting and developing scalable, distributed systems that handle high demands and complex information flows. My focus is on building fault-tolerant infrastructure using modern cloud practices and modular patterns. I excel at diagnosing and resolving intricate concurrency and scaling issues across large platforms.
Collaboration is central to my success; I enjoy working with fellow technical experts and product managers to define clear technical roadmaps. This structured approach allows the team at Softaims to consistently deliver high-availability solutions that can easily adapt to exponential growth.
I maintain a proactive approach to security and performance, treating them as integral components of the design process, not as afterthoughts. My ultimate goal is to build the foundational technology that powers client success and innovation.
Main technologies
12 years
7 Years
7 Years
7 Years
Potentially possible
Turing
This project involved the development and fine-tuning of large language models (LLMs) for tasks such as intent classification, named entity recognition (NER), and relation extraction. Python pipelines
This project involved implementing Whisper ASR to achieve accurate audio-to-text transcription. A seamless Python integration was developed to handle audio processing and interaction with Whisper. Ope
This project focused on predicting credit card churn using extensive banking data. The dataset was prepared through advanced SQL queries, followed by data cleaning using Python's Pandas library to ens
This project involved downloading Sentinel-2 data for Pakistan and integrating crop data for analysis. NDVI and other vegetation indices were calculated from satellite imagery to assess vegetation hea
Master of Science (MS) in Data Science
2023-01-01-2025-01-01
Bachelor of Computer Science (BCompSc) in Computer science
2013-01-01-2017-01-01