Ankita Muke

About Ankita Muke

Skilled in Python for data analysis (pandas, NumPy, scikit-learn), SQL for data extraction and manipulation, and Power BI for building interactive dashboards and data-driven reports. Strong in EDA, visualization, and presenting actionable insights for business decisions. Project: Loan Eligibility Automation — Credit Risk Prediction Role: Python Data Analyst / Junior Data Scientist Company: Dream Housing Finance (Case Study Project) Description: Automated the loan eligibility process for a housing finance company by developing a real-time machine learning model to predict credit risk and loan approval. Collected and analyzed customer data (income, dependents, education, loan amount, credit history, property area) to identify key factors affecting repayment risk. Highlights: Developed and deployed classification models (Logistic Regression, Random Forest, XGBoost) using Python and scikit-learn. Improved prediction accuracy by engineering features like total income and income-to-loan ratio. Performed data cleaning, EDA, and visualization to communicate insights clearly. Automated the end-to-end prediction pipeline, integrating the model with an online loan application portal for real-time eligibility checks. Achieved ~85% model accuracy, helping reduce manual loan processing time and default risk. Tools & Skills: Python, pandas, NumPy, scikit-learn, Matplotlib, Seaborn, Jupyter Notebook, EDA, Feature Engineering, Model Deployment, Credit Risk Analytics

Experience

1. Data Analysis with Python Programming Language

   Springboard

   Jan 2025 — Present · Nagpur, IN

Education

• Sant Gadge Baba Amravati University, Amravati

  Bachelor of computer application