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Data Analyst with less than a year in SQL, Power BI, and Machine Learning.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Aspiring Data Analyst with a B.E. in Computer Science Engineering and hands-on experience in SQL, Excel, Power BI, Python, and Machine Learning. Developed analytical projects involving sales analytics, customer segmentation, and predictive modeling. Skilled in data cleaning, exploratory data analysis, dashboard development, and transforming complex datasets into actionable business insights.
Sathyabama University
B.E · Computer Science Engineering
August 1, 2021 – June 30, 2025
Customer Segmentation & Behavior Analysis
June 24, 2026 – Present
Analyzed customer transaction data to understand purchasing patterns and customer preferences. Designed interactive Power BI dashboards to monitor customer retention, repeat purchases, and revenue contribution. Generated actionable insights from customer data to support targeted marketing strategies and improve customer retention.
Recipe Search and Recommendation Platform
June 24, 2026 – Present
Designed and developed a responsive web application that allows users to browse, search, and filter recipes efficiently. Organized recipe data into categories to improve accessibility and user experience. Implemented search and filtering functionality to enable quick recipe discovery.
Sales Performance Analytics Dashboard
June 24, 2026 – Present
Collected and analyzed sales data from multiple regions to identify business trends and customer purchasing behavior. Performed data cleaning, transformation, and validation to ensure data accuracy and consistency. Extracted, transformed, and analyzed structured datasets using SQL to identify sales trends and support business reporting.
Machine Learning-Based Spam Classification System
June 24, 2026 – Present
Collected and preprocessed large datasets containing spam and non-spam messages for model training and evaluation. Performed data cleaning, feature extraction, and text classification using machine learning techniques. Developed and compared multiple machine learning models including Naive Bayes, Random Forest, Decision Tree, and Support Vector Machine (SVM). Evaluated model performance using accuracy, precision, recall, and F1-score metrics to identify the best-performing classifier.
Cultural Fit Analysis
The candidate's academic projects demonstrate a proactive approach to learning and applying diverse data analysis techniques, from sales performance to customer segmentation and machine learning. This breadth of interest aligns well with a dynamic data analyst role that requires continuous learning and problem-solving. The focus on actionable insights and business reporting in projects indicates a results-oriented mindset.
Soft Skills & Operational Fit
The psychometric test score of 334/500 suggests a moderate fit in areas like logical reasoning, work attitude, stress handling, and team collaboration. The English test score of 77/100 indicates good communication clarity and professional language usage, which is beneficial for presenting analytical insights.