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Data Science with less than a year in Deep Learning, Machine Learning, and Data Analysis.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Currently completed an MSc in Applied Data Science at SRM Institute of Science and Technology, I possess a strong programming foundation with proficiency in Python, SQL, and data analysis. Passionate about problem-solving, I continuously enhance my skills in data visualization and machine learning to build efficient, data-driven solutions and contribute to innovative teams.
SRM University
M.Sc · Applied Data Science
August 1, 2024 – June 30, 2026
St.Xavier's College
B.Sc · Computer Science
August 1, 2021 – June 30, 2024
AICTEVIRTUALINTERNSHIP
AI ML training
January 1, 2026 – Present
India
Rice Leaf Disease Prediction
January 1, 2025 – June 1, 2026
Developed an image classification system using MobileNetV2 and TensorFlow to identify rice leaf diseases. Performed data preprocessing, image augmentation, feature extraction, and model optimization. Classified diseases including Bacterial Leaf Blight, Brown Spot, Leaf Blast, and Sheath Blight. Built an interactive Streamlit application for real-time disease prediction and visualization. Improved early disease detection and supported data-driven agricultural decision making.
Aloe vera leaf disease prediction
January 1, 2025 – June 1, 2026
Developed a deep learning model using Vision Transformer (ViT) to classify aloe vera leaf diseases with high accuracy. Performed data preprocessing, image augmentation, and feature extraction to improve model performance. Trained and optimized the model for accurate disease identification from leaf images. Applied computer vision techniques for automated disease detection. Improved early disease diagnosis and supported agricultural decision-making.
Stock Market Prediction Apple and Google
January 1, 2025 – June 1, 2026
Developed predictive models using historical stock market data for price forecasting. Performed data collection, preprocessing, and feature engineering on financial datasets. Conducted time-series analysis to identify trends and patterns in stock prices. Created interactive dashboards and visualizations using Tableau. Improved investment analysis through data-driven forecasting and insights.
Cultural Fit Analysis
The candidate's academic projects show a focus on practical applications of data science, particularly in agricultural and financial domains. This indicates an interest in diverse problem sets. The ongoing Master's degree and internship suggest a proactive approach to learning and skill development. However, the lack of professional experience limits the assessment of cultural fit in a corporate environment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a problem-solving mindset and a passion for building data-driven solutions. The academic projects suggest an ability to work independently on defined tasks. However, there is insufficient data to assess stress handling, team collaboration, or communication clarity in a professional setting.