Data Scientist/ML Engineer with 5 years of experience specializing in Data Analysis, Data Mining, and Machine Learning. I have a robust background in working with large datasets—structured, semi-structured, and unstructured—for data acquisition, validation, predictive modeling, and visualization. My technical proficiency spans Python, Spark MLlib, SQL, and Scikit-Learn. Throughout my career, I have actively participated in all phases of the data science project lifecycle, including data extraction, cleaning, visualization, and model development and maintenance. I possess excellent knowledge of machine learning techniques and algorithms such as logistic regression, SVM, random forests, and deep learning. I have extensive experience with the Software Development Life Cycle (SDLC) in both Waterfall and Agile methodologies. My expertise in Python visualization packages like Seaborn, Matplotlib, and Plotly has enabled me to apply machine learning solutions to a wide range of business problems effectively. I am well-versed in building machine learning models using Python libraries, including NLP libraries like NLTK and spaCy, Pandas, NumPy, SciPy, and TensorFlow. My comprehensive understanding of statistical prediction modeling, model testing, and economic forecasting approaches complements my machine learning skills. With a strong foundation in relational and NoSQL databases, data visualization tools like Tableau, and dashboard development, I excel at transforming business requirements into analytical models and data mining solutions. My proficiency extends to deep learning methods such as Artificial Neural Networks (ANN) and Recurrent Neural Networks (RNN), as well as fine-tuning transformer-based models like BERT and Large Language Models (LLM) including GPT-4 and LLAMA2. I am passionate about leveraging data to drive business decisions and enhance operational efficiencies. My goal is to continue applying my skills and experience in data science and machine learning to solve complex problems and contribute to innovative solutions.