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Data Science with 1+ years in Data Analysis & Machine Learning.
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Results-driven BCA graduate specializing in Data Analysis, Machine Learning, and Artificial Intelligence. Proficient in Python (Pandas, NumPy, Matplotlib, Seaborn), SQL, and Power BI for end-to-end data workflows including EDA, ETL, feature engineering, and predictive modeling. Experienced in transforming raw datasets into actionable business insights through data visualization and statistical analysis. Holds 5 Microsoft Azure & Power Platform certifications. Eager to contribute analytical skills to data-driven decision-making as a fresher Data Analyst.
Yenepoya University
Bachelor of Computer Applications (BCA) · Robotics, Machine Learning & Artificial Intelligence
August 1, 2022 – June 30, 2025
MES Higher Secondary School
Higher Secondary Certificate (HSC) · Computer Science
June 1, 2020 – May 31, 2022
CodeMe Hub
Data Scientist Intern
August 1, 2025 – Present
Kozhikode, Kerala, India
Skillzep Technologies Pvt Ltd
AI/ML Intern
March 1, 2025 – May 1, 2025
Mangalore, Karnataka, India
Retail Sales & Profit Forecasting System
January 1, 2025 – December 31, 2025
Developed a predictive analytics model to forecast sales and profit trends from grocery retail transactional data using Regression and Random Forest algorithms. Conducted comprehensive EDA and feature engineering identified key revenue drivers and seasonal patterns through Matplotlib and Seaborn visualizations. Delivered data-driven insights and reports that supported strategic inventory and pricing decisions, improving business performance visibility.
Telecom Customer Churn Analysis & Detection Dashboard
January 1, 2025 – December 31, 2025
Built an end-to-end churn analysis pipeline — performed EDA, statistical analysis, and classification modeling (Logistic Regression, Decision Tree) on a telecom customer dataset. Visualized churn patterns, customer segments, and risk factors using Power BI-style dashboards within a Streamlit web app, enabling real-time insight delivery. Deployed interactive web application allowing telecom teams to identify at-risk customers and drive proactive retention strategies.
View ProjectFace Mask Detection System
January 1, 2025 – December 31, 2025
Developed a real-time face mask detection system using Convolutional Neural Networks (CNN) and OpenCV for image classification. Processed and augmented image datasets, optimized the deep learning model for high accuracy across varied lighting conditions. Integrated the model with a live video feed pipeline to deliver real-time mask compliance predictions.
View ProjectInteractive Movie Recommendation System
January 1, 2025 – December 31, 2025
Built a content-based filtering recommendation engine using cosine similarity techniques on movie metadata. Engineered features from genre, cast, and description data to generate personalized movie suggestions. Developed an interactive web interface for user input, improving user engagement with real-time recommendations.
View ProjectDP-900: Microsoft Azure Data Fundamentals
Microsoft
June 1, 2026 – Present
AI-900: Microsoft Azure AI Fundamentals
Microsoft
June 1, 2026 – Present
AZ-900: Microsoft Azure Fundamentals
Microsoft
June 1, 2026 – Present
PL-900: Microsoft Power Platform Fundamentals
Microsoft
June 1, 2026 – Present
SC-900: Microsoft Security, Compliance, and Identity Fundamentals
Microsoft
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's diverse project portfolio, ranging from retail forecasting to customer churn analysis and computer vision, indicates a broad interest in applying data science across different domains. This versatility, combined with a clear alignment with the 'Data Science' target role, suggests a good cultural fit for an organization that values continuous learning and practical application of skills. The multiple Microsoft certifications also show initiative and a structured approach to skill acquisition.
Soft Skills & Operational Fit
The candidate demonstrates a proactive approach to learning and skill development through numerous certifications and personal projects. Their internship experiences highlight collaboration and problem-solving in technical environments. The project descriptions indicate an ability to translate technical work into business insights, which is crucial for operational fit in a data-driven role.