SYED MUHAMMAD ZAWWAR ASIF

AI Engineer | Data Scientist | ML Engineer | Prompt Engineer
Karachi, PK.

About

Highly accomplished AI Engineer and Data Scientist with a strong foundation in Software Engineering, seeking to leverage extensive expertise in computer vision, machine learning, and large language models (LLMs) into advanced AI/ML, Data Science, or Prompt Engineering roles. Proven ability to develop and deploy interactive, user-facing AI solutions, streamline data workflows with web automation, and lead complex, cross-functional projects, driving end-to-end system integrations for real-world challenges and measurable impact.

Work

Pakistan State Oil - HeadOffice
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Data Scientist

Karachi, Sindh, Pakistan

Summary

As a Data Scientist, Syed Muhammad Zawwar Asif automates critical reconciliation processes, analyzes sensor data for accuracy, and provides essential technical support, significantly enhancing operational efficiency and data integrity.

Highlights

Automated manual dip-read reconciliation using Selenium, reducing processing time by 90% and eliminating data entry errors.

Analyzed RTG sensor data to detect discrepancies in tank metrics (level, temperature, density), ensuring accuracy in reporting and preventing potential losses.

Provided technical support for depot operations, resolving 50+ incidents monthly and streamlining multi-bay truck loading workflows.

10Pearls
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Data Science (Intern)

Karachi, Sindh, Pakistan

Summary

As a Data Science Intern, Syed Muhammad Zawwar Asif contributed to a Telecommunication Churn Prediction project, exploring emerging technologies and enhancing professional communication skills.

Highlights

Contributed to a Telecommunication Churn Prediction project during a virtual internship, applying advanced data science techniques.

Attended weekly technical and non-technical online sessions, enhancing both domain knowledge and professional communication skills.

Explored and utilized emerging technologies, including Llama 3.2, Plotly, Seaborn, and Scikit-Learn, for data visualization and machine learning tasks.

Digital Gravity
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Project Management (Intern)

Karachi, Sindh, Pakistan

Summary

As a Project Management Intern, Syed Muhammad Zawwar Asif managed 5 simultaneous web development projects, ensuring on-time delivery and high client satisfaction through strategic planning and cross-functional collaboration.

Highlights

Managed 5 projects simultaneously, delivering websites on time with excellent client feedback and achieving high client satisfaction.

Applied strong communication, problem-solving, and strategic planning skills for efficient execution and successful project delivery.

Collaborated with cross-functional teams to optimize workflows and boost productivity, enhancing project outcomes.

The Disrupt Lab
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Junior AI Developer

Karachi, Sindh, Pakistan

Summary

As a Junior AI Developer, Syed Muhammad Zawwar Asif developed and trained machine learning models, specializing in computer vision and object detection, through advanced image annotation and processing techniques.

Highlights

Performed multiple types of image annotation using RoboFlow, creating high-quality datasets for machine learning models.

Gained proficiency in OpenCV for image processing and OCR techniques, enhancing data extraction capabilities.

Trained models on Google Colab, specializing in YOLO for real-time object detection for various applications.

Education

Sir Syed University of Engineering and Technology
Karachi, Sindh, Pakistan

BS

Software Engineering

Grade: CGPA=3.47

Publications

Optimizing Product Findings in E-commerce by Selenium and Naive Bayes Approach.

Published by

SSRN

Summary

Research focusing on enhancing e-commerce product discovery through Selenium-based web scraping and Naive Bayes classification for improved product categorization.

Certificates

Specialization in Machine Learning

Issued By

Coursera

Python Basics

Issued By

HackerRank

Skills

Technical

Python, OpenCV, Selenium, SQL, Pandas, Tesseract, HTML, CSS, JavaScript, PHP.

AI/ML

YOLO, Scikit-Learn, LLMs (OpenAI, Llama, Groq, Mistral), RAG, Random Forest, XGBoost, Naive Bayes.

Tools

Google Colab, RoboFlow, Streamlit, PyTorch, Git Version Control, Canva, Excel, MS Project.

Web Development

WordPress, Themes, Templates.

Management & Soft Skills

Project Management, Cross-Functional Collaboration, Agile Workflows, Strategic Planning, Problem-Solving, Communication.

Projects

AI-Driven CSV Insights Automation (Personal Project)

Personal

Summary

Built a no-code automation workflow in n8n to transform raw CSV files into AI-powered insights and dynamic visualizations. Integrated Groq-Kimi for trend and anomaly detection, QuickChart for automated graph generation, and email delivery for seamless reporting, enabling rapid decision-making without manual analysis.

Tank-Dip Automation & Reconciliation

Summary

Developed an automated system for fuel tank dip-read reconciliation, leveraging Python and Selenium to extract and compare data, significantly reducing manual effort and errors for improved data integrity.

Telco. Churn Prediction

Summary

Designed and implemented a churn-prediction pipeline using Scikit-Learn (Random Forest, XGBoost), achieving AUC 0.85, and created a Streamlit dashboard with a LangChain RAG assistant for conversational data exploration.

Easy Shop (Final Year Project)

Summary

Developed an e-commerce product data scraping and categorization system, leveraging Selenium for data collection and a Naive Bayes classifier for product classification with 87% accuracy.

Website ACEP & NattyCraft

Summary

Designed and developed responsive websites for clients, ensuring modern layouts and robust functionality using HTML, CSS, JavaScript, and PHP, leveraging AI for optimization.

DARAZ ID Card and Cheque Detection Model

Summary

Trained a multi-class YOLO model for international ID and cheque detection, achieving 90% plus classification accuracy, and automated dataset augmentation to improve model robustness.

Label Recognition & Text Extraction Pipeline

Summary

Created an OCR pipeline using OpenCV and Tesseract to extract text from printed labels, achieving 95%+ recognition accuracy, annotated over 5,000 images with Roboflow, and designed a Pandas-based ETL process to convert raw OCR outputs into clean, structured CSV files, reducing manual entry by 80%.

Barcode Detection & Inventory-Tracking

Summary

Developed and trained a Pyzbar-powered barcode detection model, streamlining product ID workflows, using Roboflow for dataset annotation and Google Colab for rapid model prototyping.