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Data Science with less than a year in Data Analytics & Machine 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
Currently pursuing training in Data Analytics and Machine Learning, with practical exposure to data preprocessing, model building, and visualization. Passionate about solving real-world problems using data-driven insights and analytical thinking.
Cummins College of Engineering, Nagpur
B.Tech · Computer Engineering
August 1, 2021 – June 30, 2025
V Kumar Solutions (I) Pvt. Ltd.
Data Science Intern
December 1, 2025 – Present
Pune, Maharashtra, India
Zomato Sentiment Analysis
June 24, 2026 – Present
Performed sentiment analysis on Zomato customer reviews using Kaggle dataset. Preprocessed unstructured text data and converted it into numerical features using CountVectorizer. Implemented Naive Bayes classifier to predict review sentiment (positive, neutral, negative).
ResumeQuest – Resume creation & Interview Question Generator
June 24, 2026 – Present
Analyzed resume text data to extract skills, experience, and keywords using NLP. Preprocessed text using SpaCy and NLTK for improved data quality and accuracy. Built a Python & Flask backend system for automated resume parsing using PDFMiner.
Cultural Fit Analysis
The candidate's academic projects show a proactive approach to learning and applying data science concepts. The internship, though recent, indicates an interest in gaining practical experience. The project diversity (sentiment analysis, resume parsing) suggests a broad interest within data science. The target role of 'Data Science' aligns well with the candidate's stated interests and current internship. However, the overall experience level is very junior, which might impact fit for senior roles requiring extensive industry experience.
Soft Skills & Operational Fit
The candidate's resume indicates a passion for solving real-world problems using data-driven insights and analytical thinking. The academic projects demonstrate initiative and a basic understanding of project lifecycle from data preprocessing to model implementation. However, there is insufficient data to assess specific soft skills like teamwork, leadership, or stress handling.