4+ years of experience as a Data Analyst with strong proficiency in Python, SQL, and R for data analysis, automation, and modeling. Skilled in building interactive dashboards and reports using Power BI, Tableau, and advanced Excel (VLOOKUPs, Pivot Tables, VBA). Hands-on experience in ETL development and data integration using SSIS, Apache Airflow, and Informatica. Proficient in working with databases including MySQL, PostgreSQL, MongoDB, SQL Server, AWS Redshift, and Snowflake. Experienced in cloud technologies such as AWS (S3, EC2, Lambda, Glue), GCP (BigQuery, Dataflow), and Azure Data Lake. Applied machine learning models like Logistic Regression, Random Forest, and LSTM to support predictive analytics. Strong in data wrangling, EDA, and visualization using Pandas, NumPy, Seaborn, Matplotlib, and Plotly. Knowledgeable in data warehousing, data governance, and data modeling for structured and unstructured datasets. Familiar with compliance and regulatory standards including HIPAA, GDPR, and SOX. Effective communicator with experience working in Agile/Scrum environments using tools like Jira. Adaptable across Windows, Linux, and Mac OS with solid version control and scripting experience.
Stock Market Prediction Using Machine Learning, Conducted in-depth Exploratory Data Analysis (EDA) on historical stock market data, identifying relevant features and trends. Implemented machine learning models such as Random Forest, Gradient Boosting, and Long Short-Term Memory (LSTM) networks to predict stock prices and market movements. Nations Mental Health Using Twitter Sentiment Analysis, Analyzed sentiment for user-generated tweets using effective libraries such as Tweepy and NLTKP python module like Text Blob. Implemented Naive Bayes classifier to produce results, perform analysis and various operations on the big data using RapidMiner.
Title: DATA ANALYST