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Data Analyst,Machine learning engineer with less than a year in Python, SQL & Power BI, specializing in cloud-based analytics
Aspiring Data Professional with hands-on experience in Python, SQL, Machine Learning, Data Analytics, Power BI, and cloud-based data solutions. Developed end-to-end projects spanning data collection, cleaning, exploratory data analysis (EDA), feature engineering, statistical modeling, machine learning, and interactive dashboard development. Skilled in transforming raw data into actionable insights through data visualization, predictive analytics, and business intelligence reporting. Proficient with AWS analytics services including S3, Glue, Athena, and QuickSight, with practical experience in NLP and data-driven problem solving. Passionate about leveraging Data Science, Machine Learning, and Analytics to build intelligent solutions and support strategic business decision-making.
Dhanalakshmi Srinivasan Engineering College
B.Tech · Artificial Intelligence & Data Science
August 1, 2022 – June 30, 2026
Bishop Heber Higher Secondary School
Higher Secondary · Bio Mathematics
June 1, 2020 – May 31, 2022
Pizza Sales Analytics Dashboard
June 1, 2026 – June 30, 2026
Analyzed pizza sales transaction data using MySQL to calculate key business metrics including revenue, orders, and sales performance. Developed SQL queries to identify sales trends, top-performing products, and category-wise revenue contribution. Built an interactive Power BI dashboard featuring KPI cards, sales trends, category analysis, and dynamic filters. Conducted Best Seller and Worst Seller analysis based on revenue, quantity sold, and order volume.
Customer Behaviour Analytics - MySQL & Power BI Dashboard
May 1, 2026 – May 31, 2026
Analyzed 10,000+ customer transaction records to uncover purchasing behavior and revenue trends. Developed SQL queries using joins, aggregations, and window functions to generate business insights. Built an interactive Power BI dashboard with KPI tracking, customer segmentation, product performance, and sales analysis. Identified high-value customers, top-performing products, and peak sales periods to support business decision-making.
E-Commerce Sales Analytics Dashboard
May 1, 2026 – May 31, 2026
Performed data cleaning and transformation on e-commerce sales data using Microsoft Excel. Created Pivot Tables and Pivot Charts to analyze sales, profit, customer, and regional performance metrics. Designed an interactive Excel dashboard with KPI cards, sales trends, category analysis, and dynamic slicers. Generated insights on customer purchasing behavior, profitable product categories, and regional sales performance.
Spam Detection System — NLP-Based Text Classification
March 1, 2026 – March 3, 2026
• Built an NLP-based spam detection system for SMS and email classification. • Performed text preprocessing, tokenization, stop-word removal, and TF-IDF feature extraction. • Trained and evaluated Naive Bayes, Logistic Regression, and SVM models for spam detection. • Applied SMOTE to handle class imbalance and improve spam recall. • Technologies: Python, Scikit-learn, NLTK, TF-IDF, SMOTE, SVM, Logistic Regression, Naive Bayes, Pandas, NumPy, Matplotlib, Seaborn
movie genre classification
February 4, 2026 – February 8, 2026
• Developed a machine learning model to classify movie genres using titles and plot descriptions. • Performed text preprocessing, feature engineering, and TF-IDF vectorization. • Built and evaluated a Logistic Regression model using Scikit-learn Pipeline. • Saved the trained model using Joblib and deployed a Streamlit web application for real-time predictions. • Technologies: Python, Scikit-learn, NLP, TF-IDF, Logistic Regression, Streamlit, Pandas, NumPy
Power BI - Data Visualization
Unknown
January 1, 2026 – Present
MySQL Database Fundamentals
Unknown
July 1, 2025 – Present
Machine Learning Specialization
Andrew Ng / Coursera
May 1, 2025 – Present
Natural Language Processing
Unknown
April 1, 2025 – Present
Python Programming
Unknown
March 1, 2025 – Present
Cultural Fit Analysis
The candidate's projects demonstrate a strong interest in data analysis and machine learning, aligning well with a Data Analyst role. The diversity of projects, from sales analytics dashboards to NLP-based classification and Kaggle competitions, shows a broad curiosity and willingness to explore different domains within data science. The certifications further reinforce a commitment to continuous learning. However, the lack of professional experience means cultural fit in a team or corporate environment is largely unproven.
Soft Skills & Operational Fit
The candidate's resume highlights project-based learning and application of technical skills. The descriptions suggest an ability to work independently on defined problems. However, without actual work experience or psychometric test results, it's difficult to assess stress handling, team collaboration, or broader operational fit. The focus on personal projects indicates self-motivation and a proactive learning approach.