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Data Science with less than a year in Data Analysis & Machine Learning
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Assessing your cultural and operational fit
Computer Science and Engineering graduate specializing in Data Science with hands-on experience in data analysis, machine learning, and business intelligence. Proficient in Python, SQL, Excel, Power BI, and Tableau, with a proven ability to clean, analyze, and visualize complex datasets to deliver actionable insights and drive data-driven decision-making.
Lovely Professional University
Bachelor of Technology · Computer Science and Engineering
August 1, 2022 – June 30, 2026
AI Resume Analyzer & ATS Checker
April 1, 2026 – June 1, 2026
Developed a full-stack AI-powered Resume Analyzer using React.js and FastAPI, implementing PDF parsing, ATS scoring (out of 100), skill extraction, and keyword frequency analysis across 6+ resume sections. Integrated Groq LLM to generate AI-driven resume feedback, weak section detection, action-verb enhancements, and ATS-optimized resume rewrites with downloadable DOCX output. Built a Job Description Matcher using TF-IDF similarity for JD compatibility scoring and missing keyword detection, backed by 7+ REST API endpoints with SQLite and SQLAlchemy for scalable data management.
View ProjectElectric Vehicle Adoption Prediction Using Machine Learning
February 1, 2025 – March 1, 2025
Built an EV Adoption Prediction system training 4 ML models (Naive Bayes, Random Forest, KNN, ANN) on a 500-sample synthetic dataset with 8 features including electric range, battery capacity, and government incentives. Evaluated models using Accuracy, ROC-AUC, and Confusion Matrix, identifying Random Forest as the best classifier, with Matplotlib and Seaborn visualizations for comparative performance analysis. Engineered features across 8 variables including encoded state, manufacturer, and EV type (BEV/PHEV), enabling accurate binary classification of adoption likelihood with optimized Scikit-learn pipelines.
View ProjectEV Data Analysis & Dashboarding - Tableau
January 1, 2025 – February 1, 2025
Analyzed 1,000+ EV records to identify adoption trends, year-over-year growth, manufacturer distribution, and model popularity across multiple regions. Investigated pricing trends, battery performance metrics, and government incentive impacts on consumer behavior to derive actionable market insights. Developed interactive Tableau dashboards transforming complex EV datasets into clear visualizations to support data-driven market strategy and sustainability decisions.
View ProjectExploratory Data Analysis for Machine Learning (IBM)
IBM
July 1, 2025 – Present
Deloitte Australia - Data Analytics Job Simulation (Forage)
Deloitte Australia
June 1, 2025 – Present
Core Java Training (Coding Spoon)
Coding Spoon
January 1, 2025 – Present
Data Analysis with Tableau (Coursera)
Coursera
October 1, 2024 – Present
Cloud Computing (NPTEL)
NPTEL
July 1, 2024 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong interest and foundational skill set in Data Science, Machine Learning, and Data Analysis, which aligns well with a target role in Data Science. The diversity of projects, from an AI-powered resume analyzer to EV adoption prediction and data dashboarding, shows a breadth of application and problem-solving approaches. The certifications further reinforce a proactive learning attitude. However, the lack of professional experience means cultural fit based on workplace dynamics is yet to be fully assessed.
Soft Skills & Operational Fit
The candidate's resume highlights soft skills such as analytical thinking, effective communication, collaborative teamwork, and problem-solving. The project descriptions demonstrate an ability to work on complex problems and deliver actionable insights, which aligns with operational fit for data-driven roles. The psychometric test score of 345/500 suggests moderate logical reasoning and work attitude, which could be further explored.