Data Science with less than a year in Machine Learning & Data Analytics
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 Scientist with a strong foundation in Machine Learning, Deep Learning, and Data Analytics. Skilled in Python, SQL, data preprocessing, exploratory data analysis, and predictive modeling. Passionate about transforming data into actionable insights and solving real-world problems through data-driven solutions.
University of Kerala
MSc Electronics · Artificial Intelligence
August 1, 2023 – June 30, 2025
MPMMSN Trust College,Shornur
Bsc Physics · Physics
August 1, 2020 – June 30, 2023
Luminar Technolab
Data Science Intern
February 1, 2026 – Present
Thrissur, Kerala, India
Toboids Automata Pvt. Ltd.
Robotics Engineer Intern
March 1, 2025 – August 31, 2025
India
Design of Human Eye and Facial Emotion Generation Using AI
June 18, 2026 – Present
• Developed an AI-based emotion detection system using Machine Learning and Deep Learning techniques for text emotion classification. • Trained and evaluated multiple models including SVM, LSTM, BiLSTM, CNN, and ensemble architectures, achieving 87.68% accuracy. • Performed data preprocessing, feature engineering, and model evaluation using Python and machine learning frameworks. • Implemented a stereo vision-based depth estimation system for real-time face detection and distance measurement.
Cultural Fit Analysis
The candidate's academic projects and internships align well with a Data Science role, indicating a clear career interest. The diversity of projects (emotion detection, robotics) suggests a broad interest in AI applications. The current Data Science internship further strengthens the alignment. The candidate appears to be a good cultural fit for a data-driven organization that values continuous learning and practical application of AI/ML.
Soft Skills & Operational Fit
The candidate highlights 'Quick Learner' and 'Team Work' as soft skills. The project description mentions 'Team Work'. These indicate a potential for collaborative environments and adaptability, which are positive for operational fit. However, without specific examples or further assessment, the depth of these skills cannot be fully evaluated.