
Aspiring Data Scientist | Learning Machine Learning & AI | Python | SQL | Passionate About Data-Driven Solutions | Lifelong Learner | Flutter | Firebase
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Telecom-Customer-Churn-Prediction
July 3, 2025 – July 18, 2025
Telecom Customer Churn Prediction project files
View ProjectOla-Data-Analysis
April 3, 2025 – April 5, 2025
🚖 Ola Data Analyst Project – A deep dive into Ola ride booking data using SQL, Excel, and Power BI. This project uncovers insights on ride trends, customer behavior, cancellations, revenue patterns, and ratings through data analysis and visualization. 📊📉
View ProjectTelecom-Customer-Churn-EDA
March 27, 2025 – April 5, 2025
Exploratory Data Analysis on Telecom Customer Churn dataset using Python, Pandas, Matplotlib, and Seaborn.
View ProjectCar-Price-Prediction
March 27, 2025 – April 5, 2025
🚗 Car Price Prediction using ML Predicts car prices based on factors like brand, model, year, and mileage using ML models (Linear Regression, Decision Tree, Random Forest, XGBoost). Includes data cleaning, EDA, model training, and evaluation with Python, Pandas, Matplotlib & Scikit-Learn. 🔗 Check the README for details! 🚀
View ProjectFashioRoller
December 16, 2023 – April 25, 2024
FashionRoller, is a E-Commerce Clothing app . It is developed using Flutter and Firebase as a minor project of BCA 3rd year(5th sem).
View ProjectCultural Fit Analysis
The candidate's project portfolio shows a mix of mobile development (Flutter), web development (HTML, CSS, JavaScript), and data science projects. While there's an alignment with the 'Data Scientist' target role through specific ML projects, the breadth of other projects suggests a diverse interest rather than a focused deep dive into data science. The lack of professional experience or team projects makes it difficult to assess cultural fit beyond individual initiative.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. No psychometric test results or interview feedback provided.