An engineering graduate with completion of Post Graduate Program in Data Science and Engineering possessing key skills in Data Analytics, Predictive Analytics, deriving insights from raw data, Visualization, Data Structures & Algorithms, conceptual understanding of Programming Paradigms, DBMS, Big Data, SQL, NoSQL, GraphQL & Vector Databases, APIs, Git, SDLC, Agile & CRISP-DM methodologies, basics of System Design, Backend Development, Mathematical foundation and hands-on-experience on building Machine Learning & Deep Learning models and Pipeline, understanding of Neural Network Architecture, Machine Learning Deployment (MLOps), Automation using CI/CD Pipeline, Statistical Analysis, Hypothesis & A/B Testing, Regular Expressions, building Data Pipeline, Data Extraction, Data Engineering, Data Warehousing, Data Preprocessing, Feature Engineering, Time Series Forecasting, Natural Language Processing, Prompt Engineering and Generative AI (LLM).• Tech Stack : Python, SQL, AWS, GCP, Tableau, Advanced Excel, Databricks, Apache Spark, Hadoop Ecosystem, MLflow, ONXX, HTML, CSS, JavaScript• Machine Learning : Supervised, Unsupervised, Reinforcement Learning• Deep Learning Techniques : Transfer Learning, Federated Learning• Generative AI : RAG, GAN, Auto Encoders, LLM, Transformers• Databases : MySQL, MongoDB, Neo4j, ChromaDB• Data Analytics : Predictive Analytics, Time Series Forecasting, Natural Language Processing • Libraries/Framework : Pandas, Numpy, Matplotlib, Seaborn, Plotly, Scikit-learn, Tensorflow, Keras, spaCy, NLTK, Scipy, Statsmodels, Pyspark, Langchain, DsPy, Flask, FastAPI, Django, React, Streamlit, GradioI have a very keen interest in backend development building intelligent AI systems, evaluating, optimising, integrating & deploying them into software, Predictive Analytics, Data Processing & Management and Visual Analytics.