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Data Analyst with less than a year in AI/ML & Python
Computer Science Engineering graduate (2026 Batch, CGPA: 8.16/10) with 1+ year of internship experience in Artificial Intelligence, Machine Learning, Python-based model development, and data science workflows. Proficient in Python (Pandas, NumPy, Scikit-learn, Matplotlib), SQL, EDA, data preprocessing, feature engineering, model training, and evaluation. Familiar with deep learning concepts, NLP, TF-IDF, and collaborative filtering techniques. Certified in AI & Machine Learning (Infosys Springboard) and AWS Cloud Fundamentals. Eager to work on cutting-edge AI/ML technologies and solve real-world business challenges with an innovative data-driven team.
Er. Perumal Manimekalai College of Engineering
B.E. · Computer Science and Engineering
N/A – June 30, 2026
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MOOC Recommendation System
January 1, 2025 – January 1, 2026
Developed an AI/ML-based recommendation system using Python (Scikit-learn, Pandas, NumPy) — applied collaborative filtering, TF-IDF, and NLP techniques to build intelligent, personalized content recommendations. Implemented supervised and unsupervised machine learning algorithms; performed data preprocessing, feature engineering, and EDA on user behavior datasets to train and validate ML models. Evaluated model performance using accuracy, precision, and recall metrics; applied Hugging Face Transformers for NLP-based content analysis — achieving Precision@K performance benchmarks.
SQL - Basic
HackerRank
June 1, 2026 – Present
AWS Cloud Service & Fundamentals
Amazon Web Services
June 1, 2026 – Present
Python for Data Science
NPTEL
June 1, 2026 – Present
AI & Machine Learning
Infosys Springboard
June 1, 2026 – Present
Google Analytics for Beginners
June 1, 2026 – Present
SQL Concepts
Coursera
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, including an academic recommendation system and multiple data analyst/science internships, indicates a strong interest and proactive approach to gaining experience in the data domain. Their certifications further demonstrate a commitment to continuous learning. The roles and projects align well with a data-driven culture, showing an eagerness to contribute to AI/ML-based solutions and business analytics. The focus on documenting findings and collaborating with teams suggests a good fit for a collaborative work environment.
Soft Skills & Operational Fit
The candidate demonstrates problem-solving, analytical thinking, and a curiosity for cutting-edge technology. Their experience in collaborating with cross-functional teams and documenting findings indicates good team collaboration and communication skills, which are crucial for operational fit in a data-driven environment. The project diversity and internship roles suggest an adaptable individual eager to learn and apply new technologies.