Data Science with 1+ years in AI/ML model development & data analysis.
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Assessing your cultural and operational fit
Data Science enthusiast with experience in data collection, analysis and developing machine learning / deep learning and AI models. Expertise in using SQL for database management and Python for data manipulation and analysis. Strong background in providing actionable insights through data visualization and storytelling. Solid problem solving skills and a passion for uncovering trends and patterns that drive business growth. Committed to continuous learning and staying up-to-date with the latest AI / ML tools and techniques.
APJ Abdul Kalam Technological University
B.Tech · Computer Science
August 1, 2020 – June 30, 2024
Inker Robotic Solutions Pvt. Ltd.
AI Intern
December 1, 2025 – March 1, 2026
India
Luminar Technolab
Data Science intern
September 1, 2024 – June 1, 2025
India
Football Analysis using YOLO (AI, ML)
April 1, 2025 – April 1, 2025
Detects and tracks players, referees, and footballs in video footage using YOLO, Uses optical flow to assess camera movement between frames, enabling us to accurately evaluate a player's movement, Assigns players to teams based on the colors of their t-shirts using Kmeans for pixel segmentation and clustering, With this information, we can measure a team's ball acquisition percentage in a match. Implemented perspective transformation to represent the scene's depth and perspective, allowing us to calculate a player's movement in meters rather than pixels. Calculated player speed and distance covered.
Facial Expression Recognition (Deep Learning, CNN, Web Development)
March 1, 2025 – March 1, 2025
Devoloped a CNN model using the FER2013 data set. Labeled seven emotions and split the data pixels into emotions. CNN model is built using keras sequential model. The final model detects facial expressions with an accuracy of 80.12%. It is deployed in real time and hosted as a web app using streamlit.
Weather Prediction (EDA, Supervised Learning, Streamlit Web App)
February 1, 2025 – February 1, 2025
A Weather prediction model which was trained using 8 classification models and applied oversampling, performed hyperparameter tuning and finally obtained an accuracy of 97.40% in Random Forest Classifier & Hosted as a web app using Streamlit.
Python 101 for Data Science
IBM
December 1, 2024 – Present
University approved college project
Unknown
April 1, 2024 – Present
Volunteer at HackAthena, Hackathon contducted by CESA, JECC Kerala, India
CESA, JECC Kerala, India
April 1, 2024 – Present
NASA Space Apps challenge participation
NASA
October 1, 2023 – Present
Volunteer at NASA Space Apps Challenge Global Hackathon Thrissur, Kerala
NASA
October 1, 2023 – Present
NPTEL MOOC Programming in JAVA
NPTEL
April 1, 2022 – Present
Cultural Fit Analysis
The candidate's project diversity, including weather prediction, facial recognition, and football analysis using YOLO, demonstrates a broad interest in applying data science and AI across different domains. Participation in hackathons (NASA Space Apps Challenge, HackAthena) and volunteer roles indicates a proactive and community-oriented mindset, which aligns with a collaborative and innovative culture. The internships, though short, show an eagerness to gain practical experience and apply academic knowledge in industry settings. The target role of Data Science aligns well with the candidate's academic background, project work, and internship experiences, particularly in ML, DL, NLP, and data analysis.
Soft Skills & Operational Fit
The candidate lists 'Adaptive, Time Management, Communication, Flexibility, Leadership, Collaboration' as soft skills. While these are valuable, the provided data does not offer specific instances or evidence to evaluate their proficiency in these areas. The project descriptions indicate an ability to complete complex technical tasks, which indirectly suggests good time management and problem-solving. The academic nature of most projects and internships suggests a learning-oriented and collaborative approach, fitting well into a team environment.