Kruti Enugu

Data Science graduate with strong analytical and technical skills, specializing in operational and housing dataset analysis to provide actionable insights. Proficient in Python, SQL, and Excel, with a solid foundation in statistical modeling. Demonstrated ability to collaborate effectively in team environments and adapt quickly to new tools. Seeking entry-level data analyst and research internship opportunities to leverage skills in supporting public programs and policy decisions.

Mobile Phone Activity Analysis: Analyzed large-scale mobile phone Call Detail Records (CDRs) to study communication patterns across a city

• Cleaned and prepared raw datasets to ensure accuracy for analysis
• Performed exploratory data analysis (EDA) to understand call, SMS, and internet usage trends

Housing Price Prediction System:

Processed and analyzed Ames Housing dataset with 1460 records and 74 numerical/categorical features., Conducted feature selection and correlation analysis to identify key price predictors (e.g., OverallQual, GrLivArea, GarageCars).

• Developed predictive models using Linear Regression, Ridge, Lasso, Random Forest, XGBoost, and Polynomial Regression.

Tax and Payment Tracking System: Managed and processed 11+ company tax records including amount, due date, payment date, and status (paid/unpaid)., Performed data cleaning and validation to handle missing or inconsistent records.