👤 SUMMARY

<aside> <img src="/icons/question-mark_gray.svg" alt="/icons/question-mark_gray.svg" width="40px" /> Who Am I

https://youtu.be/tIHN3eD1SMI

Hey there, Myself Omkar Pawar, and I'm on this exciting journey called data science. Yep, the one that involves numbers, algorithms, and all that good stuff. I have experience with Python and have delved into algorithmic exploration. My dream is to use data to create amazing things. Let's have a conversation about data, algorithms, and anything else related to the world of data science! just…

and I'll transform it into a chatty parrot, speaking the language of insights.

#open_for_opportunities #data_analyst #machine_learning

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🧑‍💻 PROJECTS

<aside> <img src="/icons/push-pin_gray.svg" alt="/icons/push-pin_gray.svg" width="40px" /> Customer Segmentation with RFM Analysis

Tech Stack: Python, RFM analysis, K-Means ++, Power BI

• Assessed data quality and completeness, ensuring reliable insights for downstream analysis.
• Leveraged RFM analysis and K-Means++ clustering to identify high-value customers and their characteristics.
• Developed Power BI dashboard to effectively communicate key findings. Contributing to a significant increase in targeted conversion rate.

https://github.com/omkarpawar1430/KPMG-Virtual-Internship

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<aside> <img src="/icons/push-pin_gray.svg" alt="/icons/push-pin_gray.svg" width="40px" /> Sales Store Analysis

Tech Stack: Power BI

• Orchestrated an in-depth examination of retail store sales data, overseeing data cleaning and processing procedures.
• Employed Power BI to craft an interactive dashboard for comprehensive insights.
• Derived actionable insights, presenting strategic recommendations for store performance improvement.

https://github.com/omkarpawar1430/Ecommerce-Sales-Dashboard

https://youtube.com/shorts/Wg3fN-ShPbw?si=1YRzSlDZppHRNlKk

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<aside> <img src="/icons/push-pin_gray.svg" alt="/icons/push-pin_gray.svg" width="40px" /> Churn Analysis on E-commerce Dataset

Tech Stack: Python, Seaborn, Matplotlib

• Led a comprehensive data analyst project focused on understanding and mitigating customer churn.
• Applied data analysis techniques to scrutinize user behavior, purchase patterns, and engagement metrics.
• Employed Python alongside essential libraries for meticulous data cleaning and visualization.

https://github.com/omkarpawar1430/Customer-Churn-Analysis

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<aside> <img src="/icons/push-pin_gray.svg" alt="/icons/push-pin_gray.svg" width="40px" /> Heating Load and Cooling Load Prediction for Residential Buildings

Tech Stack: Python, Pandas, Random Forest, Flask

• Led a comprehensive energy efficiency initiative, utilizing advanced statistical modeling technique random forest.
• Conducted hyperparameter tuning to optimize model performance and Implemented feature engineering strategies for a nuanced understanding of energy consumption patterns.
• Developed a dynamic Flask-based web application for user-friendly interaction with the models.
• Leveraged Pandas for efficient data manipulation, Matplotlib for insightful visualizations, and documented the entire process for knowledge transfer within the team.

https://github.com/omkarpawar1430/Energy-Efficiency-with-Linear-Regression-Vs-Random-Forest

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<aside> <img src="/icons/push-pin_gray.svg" alt="/icons/push-pin_gray.svg" width="40px" /> Diamond Price Prediction

Tech Stack: Python, Seaborn, Matplotlib, Ridge, Lasso and Elastic Net Regression, Flask

• Engineered a sophisticated machine learning model for predicting diamond prices.
• Employed regression techniques like Linear Regression, Ridge, Lasso, and Elastic Net.
• Conducted thorough model evaluations and selections, achieving an elevated level of accuracy

https://github.com/omkarpawar1430/Diamonds-Price-Predictions

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<aside> <img src="/icons/push-pin_gray.svg" alt="/icons/push-pin_gray.svg" width="40px" /> YouTube Scraper

Tech Stack: Python, Selenium

• Engineered a specialized web scraper to extract data from YouTube using Selenium.

https://github.com/omkarpawar1430/YouTube-Web-Scrapper

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🥷 SKILLS

<aside> <img src="/icons/checkmark-line_gray.svg" alt="/icons/checkmark-line_gray.svg" width="40px" /> Programming Languages: Python, SQL

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<aside> <img src="/icons/checkmark-line_gray.svg" alt="/icons/checkmark-line_gray.svg" width="40px" /> Database: MySQL, MongoDB

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<aside> <img src="/icons/checkmark-line_gray.svg" alt="/icons/checkmark-line_gray.svg" width="40px" /> Tools: MS Excel, Power BI, Google Sheets, Looker Studio, Notion, Power Query, DAX, ETL, Git, GitHub

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<aside> <img src="/icons/checkmark-line_gray.svg" alt="/icons/checkmark-line_gray.svg" width="40px" /> Libraries: Pandas, Numpy, Seaborn, Matplotlib, Scikit-learn, SciPy, BeautifulSoup, Selenium, Flask Web framework

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<aside> <img src="/icons/checkmark-line_gray.svg" alt="/icons/checkmark-line_gray.svg" width="40px" /> Tasks: Web Scraping, Exploratory Data Analysis, Data Cleaning, Data Preprocessing, Data Visualization, Feature Engineering, Machine Learning, Optimization and Fine-Tuning, Predictive Analytics, Statistical Analysis, Time Series Analysis, A/B Testing

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📺 Data Decides 📈

<aside> <img src="/icons/preview_gray.svg" alt="/icons/preview_gray.svg" width="40px" /> https://www.youtube.com/@datadecides

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