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AI Engineer with less than a year in Data Science, skilled in Python, Machine Learning, and Business
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Recent Master's graduate in Data Science with a strong foundation in Artificial Intelligence, Machine Learning, and Business Intelligence tools including Python, SQL, Tableau, and Power BI. Proven ability to design and implement AI-based systems for real-world problems, as demonstrated by projects in traffic surveillance accident detection and HR analytics. Eager to apply analytical and modeling skills to drive data-driven insights and solutions.
Loyola Academy Degree and Pg College
Master of Data Science · Data Science
August 1, 2021 – June 30, 2023
Bhavan's Vivekananda Degree College
Bachelor of Science · Statistics
August 1, 2018 – June 30, 2021
A VISION-BASED SYSTEM DESIGN AND IMPLEMENTATION FOR ACCIDENT DETECTION AND ANALYSIS VIA TRAFFIC SURVEILLANCE VIDEO
June 1, 2026 – Present
Developed an AI-based system for automatic traffic accident detection and analysis using surveillance video data. Implemented Motion Interaction Field (MIF) to detect vehicle collisions based on motion patterns and object interactions. Utilized YOLO v3 for real-time object detection and localization of crashed vehicles. Reconstructed pre-collision vehicle trajectories using hierarchical clustering techniques. Applied perspective transformation to project trajectories into a vertical (bird's-eye) view for clear accident analysis. Estimated vehicle speeds using the Unbiased Finite Impulse Response (UFIR) filter for noise-robust velocity calculation. Analyzed collision angles and velocities to assist in post-accident investigations. Deployed the complete framework on a Huawei HiKey970 AI demo board, demonstrating real-time embedded AI implementation. Successfully tested the system using multiple real-world surveillance videos, achieving accurate crash detection and trajectory recovery.
LANGUAGE EXAM RESULTS
June 1, 2026 – Present
Built a model to predict the result of the exam based on the given input data features by using Machine Learning Algorithms Developed a machine learning model to predict language proficiency levels (Beginner, Medium, Fast) based on input scores from reading, listening, writing, and speaking. Preprocessed and normalized language skill data to improve prediction accuracy and model generalization. Evaluated multiple classification algorithms (e.g., Decision Tree, Random Forest, SVM, KNN) and selected the best-performing model based on accuracy, precision, and F1-score. Implemented data visualization and feature analysis to interpret model predictions and enhance model transparency. Achieved 98% accuracy on Random forest, demonstrating effective categorization of language learners by proficiency level.
HR ANALYTICS DASHBOARD
June 1, 2026 – Present
Created an HR Analytics Dashboard using Power BI and Excel to analyze workforce data and support strategic HR decision-making. Cleaned, transformed, and visualized employee data to identify key insights on demographics, salary trends, and departmental distribution. Discovered critical insights such as average employee age (36.92), highest employee concentration in Sales Executive (326), and overtime trends by gender. Highlighted organizational trends like department-wise distribution (e.g., Lifesciences with 606 employees) and average salary hike (15.21%) to aid HR planning. Enabled data-driven recommendations to improve employee retention, optimize workforce allocation, and enhance satisfaction. Collaborated with HR teams to align dashboard insights with organizational goals and employee engagement strategies.
Python for Data Science
NPTEL
June 1, 2026 – Present
Machine Learning
NPTEL
June 1, 2026 – Present
Introduction to Data Science
Cisco
June 1, 2026 – Present
Google Analytics Certification
June 1, 2026 – Present
Advance Google Analytics
Google Analytics Academy
June 1, 2026 – Present
Data Science Course
Data Minds Analytics
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects demonstrate a strong alignment with an AI Engineer role, particularly in machine learning, computer vision, and data analysis. The diversity of projects (language proficiency prediction, traffic accident detection, HR analytics) shows a broad interest and capability in applying AI/ML across different domains. The academic focus of all projects suggests a learning-oriented individual, but also indicates a potential need for exposure to industry best practices, MLOps, and collaborative development workflows.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex, multi-faceted problems, suggesting strong problem-solving skills. The collaboration with HR teams on the HR Analytics Dashboard project implies teamwork and communication skills. The academic nature of all projects means real-world operational fit and experience in production environments are not explicitly demonstrated.