Hello! I'm Mayank, a Senior Data Scientist with over 5 years of hands-on experience building and deploying machine learning systems at scale for companies like CIBC and Capgemini. I've worked on the entire end-to-end ML lifecycle—from building churn prediction models with XGBoost and fine-tuning BERT models with PyTorch, to deploying real-time Computer Vision systems on the edge (ONNX) and architecting RAG/LLM applications on Azure. My specialty? I bridge the gap between textbook data science and real-world industry applications. I know what it really takes to get a model from a Jupyter notebook into a scalable, monitored, and automated production pipeline. I've built and managed the very systems companies are hiring for, using tools like Azure, Databricks, Spark, Airflow, MLflow, and Kubernetes. If you're an aspiring Data Scientist, AI Engineer, or ML Engineer, I'm here to help you navigate the journey. I don't just teach theory; I show you how it's applied in the real world. How I can help you: AI/ML Career Roadmaps: Creating a step-by-step plan tailored to your goals. Technical Interview Prep: Mock interviews and deep dives on SQL, Python, and ML concepts (from regression to deep learning). Behavioral Interviews: Mastering the "tell me about a time..." questions with compelling stories from your projects. Real-World Projects: Brainstorming and structuring projects that look like what we build in the industry. "From Notebook to Production": Understanding CI/CD, model monitoring, drift detection, and the full MLOps lifecycle. Let's connect and build your practical path into the AI domain!