Muzahid Qureshi

Hello! I'm Muzahid Qureshi, a passionate data scientist with a keen interest in machine learning and artificial intelligence.

During my master’s program at NIT Trichy, I stumbled upon a field called materials informatics—where data science meets material discovery. I was amazed at how algorithms could assist in scientific breakthroughs. That moment became a turning point. I started learning everything I could about data science, machine learning, and AI. What began as a side interest soon became my career focus, and I’ve been exploring this exciting world ever since.

In my journey so far, I’ve built a solid foundation in Python and its data-centric libraries. I'm comfortable working with SQL for data querying and have hands-on experience with core machine learning algorithms using scikit-learn, as well as deep learning concepts using keras.

On the MLOps side, I have experience with tools like DVC and MLflow for pipeline management and experiment tracking. I understand how to design and expose ML models through tools like FastAPI, containerize them using Docker, and deploy them to the cloud like AWS. I’ve also worked with GitHub Actions for setting up CI/CD pipelines, enabling automated testing and deployment workflows. Additionally, I have hands-on knowledge of Kubernetes deployments, particularly using Minikube for local development and orchestration.

Besides data science, I enjoy working out and traveling. I understand both English and Hindi.

As a Data science professional at a Data & AI company, I worked on projects involving customer analytics and machine learning. It allowed me to grow my skills in data analysis, model development, and working with cross-functional teams to translate business problems into data-driven solutions.