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Data Science with less than a year in Python, Machine Learning, Deep Learning, NLP, and Power BI.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
M.Sc. Computer Science (AI) graduate skilled in Python, SQL, Machine Learning, Deep Learning, NLP, and Power BI. Experienced in developing AI solutions including BERT-based Fake News Detection and satellite imagery classification using ResNet101. Seeking an entry-level Data Scientist or AI/ML Engineer role.
Central University of Kerala
M.Sc. in Computer Science (Artificial Intelligence) · Computer Science (Artificial Intelligence)
July 1, 2024 – May 31, 2026
Calicut University
Bsc Computer Science · Computer Science
August 1, 2021 – May 31, 2024
Luminar Technolab
Data Science Intern
May 1, 2025 – June 30, 2025
Cochin, Kerala, India
BERT with Differential Evolution Optimization for Accurate Fake News Detection
January 1, 2026 – December 31, 2026
Built an NLP-based fake news detection system using BERT for feature extraction and text classification. Implemented Differential Evolution optimization to tune hyperparameters and improve classification performance. Achieved accurate classification of fake and real news articles using deep learning and natural language processing techniques.
Landslide Prediction Using Satellite Imagery
July 1, 2025 – November 30, 2025
Developed a landslide prediction model using satellite imagery and deep learning techniques for automated landslide classification. Applied image preprocessing, data augmentation, and feature extraction methods to improve model performance and detection accuracy. Evaluated CNN-based approaches for disaster prediction and environmental monitoring applications.
View ProjectHouse Price Prediction
January 1, 2025 – December 31, 2025
Developed a machine learning model to predict house prices based on property features and historical housing data. Performed data cleaning, exploratory data analysis, and feature engineering to improve prediction accuracy. Implemented Linear Regression and evaluated model performance using standard regression metrics.
Cultural Fit Analysis
The candidate's academic projects demonstrate a proactive approach to learning and applying diverse data science techniques, which aligns with a culture of continuous improvement and innovation. The focus on AI and ML projects, including environmental monitoring and fake news detection, suggests an interest in impactful applications. The internship provides some exposure to a professional work environment. However, the lack of non-academic or team-based projects makes it challenging to fully assess collaboration and broader cultural fit.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex problems and apply various data science techniques. The internship experience suggests a foundational understanding of data-driven problem-solving and reporting. However, without specific behavioral assessment data, it's difficult to fully assess soft skills like teamwork, stress handling, or communication beyond what's inferred from project descriptions.