Data Science with less than a year in Machine Learning & Deep 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
Undergraduate with hands-on experience in Python, Neural Networks, Data Analysis and Image Processing. Applies clean coding practices, analytical thinking and problem-solving to implement and testing efficient technical solutions. Possesses working knowledge of machine learning and computer vision concept, with an interest in contributing to project-driven teams and supporting the software development of reliable, user-focused applications.
SRM Institute of Science and Technology
B.Tech · Electronics and Communication Engineering
August 1, 2022 – June 30, 2026
National Institute of Technology
Research Associate
June 1, 2024 – July 1, 2024
Tiruchirappalli, Tamil Nadu, India
AI-Powered Elephant Alert and Bee Sound Deterrent Network
January 1, 2026 – May 1, 2026
Developed a distributed wildlife monitoring system using Raspberry Pi with 2+sensors (camera and acoustic) interfacing. Pioneering edge-based image and acoustic processing algorithms on Raspberry Pi with deep learning model (YOLO) for frame detection, by triggering bee-sound deterrent within 3 seconds of elephant detection, with 92% accuracy. Processing real-time sensor data(~10-15 frames/sec) and enabled automated alert system, improving response efficiency by ~85%.
Auto Tolling System
June 1, 2025 – August 1, 2025
Developed an Auto Tolling System using Python, OpenCV and Flask API, processing real-time video streams (15–20 FPS). Implemented ANPR with OCR, achieving 85-90% recognition accuracy under varying lighting and angle conditions. Automated vehicle detection and toll processing, reducing manual intervention by ~80% with dashboard for data management.
Plant Disease Detection System
November 1, 2024 – December 1, 2024
Developed and deployed a Plant Disease Detection System using Python, Machine Learning, Image Processing and Streamlit. Implemented computer vision techniques for early identification of crop diseases from more than 100,000 leaf images as data. Trained CNN model over multiple epochs (20–30 iterations), improving model accuracy 91%+ for classification performance.
Principles of Generative AI Certification
Infosys Springboard
May 1, 2026 – Present
Data Analytics Job Simulation
Deloitte Australia
March 1, 2026 – Present
Introduction to SQL
Simplilearn
August 1, 2025 – Present
Python for Data Science (Elite)
NPTEL
January 1, 2025 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong interest in applying AI/ML to diverse real-world problems, from wildlife monitoring to plant disease detection and auto-tolling. This project diversity, coupled with a research internship, indicates an inquisitive and adaptable mindset. The skills acquired align well with a Data Science role, showing a breadth of technical exposure relevant to the field. The academic background in Electronics and Communication Engineering, combined with data science certifications, suggests a multidisciplinary approach to learning and problem-solving.
Soft Skills & Operational Fit
The candidate's project descriptions highlight problem-solving, analytical thinking, and the ability to implement technical solutions. Collaboration is mentioned in the research associate role. The focus on practical applications and efficiency improvements in projects suggests a results-oriented approach. However, without specific behavioral assessment data, a comprehensive evaluation of soft skills and operational fit is limited.