Data Analytics with less than a year in data analysis, SQL querying, and building data-driven system
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Final-year B.Tech (AI & ML) student with demonstrated experience in data analysis, SQL querying, and building data-driven systems. Proficient in Python, Pandas, and scikit-learn for data processing; skilled in data visualization and deriving actionable insights. Familiar with Google Data Analytics tools and Excel-based reporting. Active competitive programmer with 250+ problems on CodeChef and 100+ on LeetCode. Seeking a fresher Data Analyst role to contribute to data-driven decision-making.
Manakula Vinayagar Institute of Technology, Puducherry
B.Tech · Artificial Intelligence & Machine Learning
January 1, 2022 – January 1, 2026
Tamil Plagiarism Detection System
June 19, 2026 – Present
Analyzed large Tamil text datasets using TF-IDF, cosine similarity, and morpheme-level tokenization to detect plagiarism; achieved 15% accuracy improvement over baseline. Designed modular preprocessing pipelines for normalization and rephrasing detection; performed precision-recall trade-off analysis across multiple classifier configurations. Tracked all experiment runs with structured result documentation — compared feature engineering strategies (n-grams, cosine similarity, morpheme tokenization) against quantitative metrics.
Phoneme-Level Sign Language Detection System
June 19, 2026 – January 1, 2026
Built end-to-end ML pipeline mapping 44 phoneme classes (~85% accuracy); managed full data lifecycle — annotation (Roboflow), training, evaluation, and inference. Applied Precision/Recall/F1 metrics with cross-validation; hyperparameter tuning reduced processing time by 20%; maintained reproducible experiment documentation. Research published at ICSCAN 2026: "Breaking the Silence: A Phoneme-Level Sign Language Translation Framework using YOLO-Based Gesture Detection and CMU Pronouncing Dictionary Mapping."
AI-Powered Code Refactoring VS Code Extension
June 19, 2026 – Present
Benchmarked multiple LLM configurations using quality metrics to identify the optimal prompt-model setup; reduced debugging effort by 30%. Applied prompt engineering for context-aware code improvements; deployed with CI/CD-based automated testing for continuous quality monitoring.
Python for Data Science & ML Bootcamp
Udemy
June 1, 2026 – Present
DBMS – Fundamentals & Advanced Concepts
Scaler
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects show a strong inclination towards data-driven problem-solving and innovation, aligning well with a data analytics culture. Their involvement in organizing technical events suggests a proactive and engaged personality, which can contribute positively to team dynamics. The diversity of projects, from NLP to computer vision and LLM applications, indicates a broad interest in AI/ML domains, which can be beneficial for cross-functional collaboration. However, the lack of professional experience means their adaptability to specific company cultures and corporate work ethics is an area for further assessment.
Soft Skills & Operational Fit
The candidate demonstrates strong analytical and problem-solving skills through competitive programming and project work. Their experience leading technical events suggests organizational capabilities and potential for teamwork. The focus on reproducible experiment documentation and structured result tracking indicates an organized and detail-oriented approach to work. However, without direct work experience, their operational fit in a corporate environment regarding collaboration, stakeholder communication, and project management is yet to be fully validated.