• Possess over 4 years of experience in the IT industry, specializing in Machine Learning, Data Mining with large datasets, both structured and unstructured, and executing Data Acquisition, Data Validation, Predictive Modeling, and Data Visualization• Demonstrated proficiency in OOP programming languages like Python, Java, JavaScript, and C++• Skilled in designing, building, and querying both RDBMS and NoSQL databases including PostgreSQL, BigQuery, Oracle, MS SQL, MySQL, MongoDB, HBase, and Cassandra• Highly adept in conducting exploratory data analysis using data visualization tools and libraries such as Tableau, ggplot2, Looker Studio, Seaborn, Matplotlib, and d3.js to create insightful dashboards and charts• Experienced in developing and optimizing foundational machine learning models, including regression, random forests, decision trees, boosting techniques like GBM and XGBoost, as well as neural networks, hidden Markov models, conditional random fields, and Markov random fields• Advanced in deploying Deep Learning models across various domains including image, audio, video, and tabular data. Expertise includes training, hyperparameter tuning, testing, and evaluating complex models such as CNNs, RNNs, YOLO, RCNN, and LSTMs, using PyTorch and TensorFlow frameworks• Proficient in executing Natural Language Processing (NLP) tasks such as Sentiment Analysis, Named Entity Recognition, and Text Classification utilizing state-of-the-art Large Language Models like GPT-4, LLAMA-2, PaLM-2, and Gemini 1 Pro• Proficient with creating end-to-end Machine Learning/Deep Learning pipeline and MLOps which includes ETL pipelines, Automated Model Training, Model Monitoring, Scalable Model Serving, Data Drift detection and continuous training using tools like Apache AirFlow, Kubernetes, Jenkins, Tecton, Docker, and Grafana