Headline

Aspiring Data Analyst | Exploring Data Science & Data Engineering | Python | SQL | ML | Real-World Data Projects | Open to Internships

About

I am an aspiring Data Analyst with interests in Data Science and Data Engineering, focused on turning data into meaningful insights. I am currently building real-world data projects involving data analysis, machine learning, and problem-solving. I serve as an NEP Saarthi Student Ambassador and a Board of Studies member at GD Goenka University, contributing to academic and student initiatives. I have completed an internship at the Avishkar Centre for Innovation and Incubation at GD Goenka University, where I gained exposure to innovation-driven environments and practical problem-solving. I am skilled in Python, SQL, and data analysis, and I am actively seeking internships and opportunities where I can apply my skills to solve real-world problems and grow as a data professional.

Location

Bhopal

Work experience

IBM Summer Project at IBM, Jun 2025 - Aug 2025 · 3 mos, • Built a predictive machine learning model on the Titanic dataset to classify passenger survival using supervised learning techniques. • Performed data cleaning and preprocessing including handling missing values, encoding categorical variables, and feature scaling. • Conducted exploratory data analysis (EDA) to identify key survival factors such as age, gender, and passenger class. • Implemented models like Logistic Regression, Decision Tree, and Random Forest, and compared their performance. • Achieved improved prediction accuracy through feature engineering and hyperparameter tuning. • Utilized Python, Pandas, NumPy, Matplotlib, Seaborn, and Scikit-learn for analysis and model building.

Summer Intern at GD Goenka University, Jun 2025 - Jul 2025 · 2 mos, Gurugram, • Developed a machine learning-based model to predict real estate prices using Python and regression techniques. • Performed data preprocessing, cleaning, and Exploratory Data Analysis (EDA) to identify key factors influencing property prices. • Built and evaluated predictive models to improve accuracy and generate reliable price estimates. • Designed a basic recommendation system to suggest properties based on user preferences and data insights. • Utilized libraries such as Pandas, NumPy, and Matplotlib for data analysis and visualization.

IBM Social Internship Project at IBM, Jun 2024 - Aug 2024 · 3 mos, • Analyzed employee attrition dataset to identify key factors influencing employee turnover using data-driven techniques. • Performed data preprocessing including handling missing values, encoding categorical features, and outlier detection. • Conducted exploratory data analysis (EDA) to uncover trends related to job satisfaction, salary, work-life balance, and tenure. • Built and evaluated classification models such as Logistic Regression and Decision Tree to predict employee attrition. • Identified critical drivers of attrition and provided actionable insights to improve employee retention strategies. • Created data visualizations and dashboards using Matplotlib/Seaborn to effectively communicate findings. • Tools used: Python, Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn

Education

Bachelor of Technology in Computer Science Engineering, Data Science, GD Goenka University