Muhammad Ahmed Javed

I am a Data Scientist and Machine Learning Engineer with hands-on experience building real-world AI systems, developing end-to-end ML pipelines, and solving data-driven problems across NLP, computer vision, and geospatial analysis. My journey into data science began with a fascination for how data can be transformed into meaningful insights and scalable solutions—an interest that has evolved into a strong technical foundation, backed by academic training and industry-level project experience.

I have completed my Bachelor of Science in Data Science at NUCES-FAST, where I have gained a deep understanding of statistical modeling, machine learning, and data engineering. Over the years, I have honed my skills in Python, MySQL, ETL pipeline development, statistical analysis, and transformer-based architectures. My work reflects my passion for transforming raw data into actionable intelligence.

Professionally, I have worked as a Machine Learning Engineer at Omdena, where I collaborated with global teams on AI challenges related to remote sensing, urban planning, and climate resilience. I contributed to designing ETL pipelines, optimizing ML models, annotating geospatial imagery, and evaluating deep learning frameworks such as U-Net. These experiences strengthened my ability to work in diverse, cross-functional environments and solve real-world problems at scale.

My academic work further demonstrates my versatility. For my Final Year Project, I developed a complete mosquito habitat surveillance system using Sentinel-2 imagery, YOLOv12, Roboflow, and a custom dashboard integrating a relational database. I also incorporated a Large Language Model to enable natural language querying—bridging structured data with conversational AI. Other projects include abstractive text summarization using T5, BART, and PEGASUS; air quality prediction using deep learning; and multiple remote sensing research contributions through Omdena.

Across my projects, I emphasize clean data processing, robust model evaluation, reproducible pipelines, and deployment-ready solutions. I am comfortable working with tools like TensorFlow, Scikit-learn, Hugging Face, SQL Server, Pandas, Plotly, Roboflow, and Google Earth Engine.

Beyond my technical background, I am continuously improving my communication and collaboration skills, supported by experience working with distributed teams through Trello, Slack, Google Meet, and Git. I am fluent in English, a native Urdu speaker, and progressing well in German (A2 level, with B1 planned).

Driven, curious, and committed to growth, I aim to contribute to impactful AI solutions—particularly in domains where data science can create measurable positive change.