Detail-oriented Software Engineer with 4 years of experience in Python, SQL, and cloud data systems. Experienced in building ETL pipelines, managing data workflows, and deploying solutions on AWS. Focused on delivering efficient, scalable solutions that support data-driven decision-making.
Data Science & Machine Learning Complete Course
Amazon sentimental analysis using NLP, Analyzing reviews from amazon and classifying feedback 1 as bad and 0 and good. The process involved removing stop-words, applying stemming and lemmatization, and vectorizing the words. We also utilized oversampling techniques and implemented the Multinomial algorithm. This approach resulted in achieving an accuracy of 93%. AI-Powered Color Pattern Discovery in Property Listings, Built an AI-driven tool to analyze and visualize color combinations in real estate property data. Used SQL CTEs to extract unique color patterns from the property column, leveraged OpenAI's language model to semantically group and label colour themes. Applied clustering algorithms (K-Means) to identify dominant colour trends. Deployed an interactive Streamlit app to explore clusters and visualize colour palettes.
Python (Pandas, NumPy, SQLAlchemy), SQL, Bash, HTML5, CSS3, ETL Pipelines, Data Ingestion, Data Transformation, Data Modelling, API Integration, SFTP, SnapLogic, AWS (EC2, S3, IAM, Lambda), Snowflake, Azure, MS-SQL (Yardi Systems), Snowflake, PostgreSQL, MySQL, Power BI, Tableau , Data Alerts & Dashboards, Git, CI/CD, Linux Server Management, Jupyter, VS Code, GitHub, Jira, Confluence