- Conducted exploratory data analysis (EDA) on various projects such as Retail Sales Data, Customer Segmentation, Sentiment Analysis, and Fraud Detection.- Utilized machine learning algorithms for predictive analytics in tasks like Wine Quality Prediction and House Price Forecasting.- Leveraged Python, Pandas, and NumPy to effectively clean and manipulate data, ensuring robust datasets for analysis.- Developed impactful data visualizations using Power BI and Matplotlib to communicate actionable business insights.- Employed web scraping techniques via BeautifulSoup and Selenium to extract data from online sources for analysis.- Applied SQL and MySQL for efficient database management, while using MongoDB to handle unstructured data storage.- Enhanced decision-making processes through statistical analysis, driving data-informed business strategies.

Data Analyst | Machine Learning EnthusiastKey Projects:Predict Restaurant Ratings: Built a model to forecast restaurant ratings using customer reviews, cuisine, and location data. Applied regression techniques and feature engineering for accurate predictions.Restaurant Recommendation System: Developed a personalized recommendation engine using collaborative and content-based filtering to enhance customer engagement.Cuisine Classification: Implemented NLP techniques to classify cuisines from menu data, using Python, Random Forest, and SVM for high-accuracy results.

Job responsibilities:Identified and engaged with new customers, establishing valuable connections in the market.Led marketing initiatives to generate leads and increase brand visibility.Collaborated with teams to develop strategies for customer acquisition and market penetration.Analyzed market trends and competitor activities to inform strategic decision-making.