Data Analyst with 2+ years in ML Pipelines & Interactive Dashboards
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Assessing your cultural and operational fit
3rd-year Data Science student with hands-on experience building end-to-end ML pipelines and interactive dashboards. Developed a credit risk classifier achieving ROC-AUC 0.90 on real banking data using XGBoost and advanced feature engineering. Proficient in Python, SQL, and Power BI. Seeking a data analyst internship where I can turn messy real-world data into decisions that matter.
Oriental Institute of Science & Technology
Bachelor of Technology · Data Science
August 1, 2023 – June 30, 2027
Credit Risk & Loan Delinquency Predictor
January 1, 2025 – January 1, 2026
Built an XGBoost classification model on real-world banking data to predict consumer loan default risk, handling severe class imbalance through SMOTE and threshold tuning. Engineered 15+ features from raw transaction data; performed full preprocessing pipeline including missing value imputation and encoding. Achieved F1-Score of 0.80 and ROC-AUC of 0.90 — providing a data-driven framework to flag high-risk applicants. Delivered an interactive ipywidgets dashboard for risk officers to query high-risk applicant flags in real time.
Predictive Property Pricing & Market Sentiment Dashboard
January 1, 2024 – December 1, 2024
Built a regression model to predict residential property prices from location, size, and market features; compared Linear Regression, Random Forest, and Gradient Boosting. Designed a 3-page Power BI dashboard covering market sentiment trends, seasonal sales patterns, and price distribution. Automated the ETL pipeline from raw CSV ingestion to cleaned, model-ready data frames, reducing manual prep time by ~70%.
Data Visualization with Python
IBM Skills Build
January 1, 2025 – Present
Job Simulation in Data Analytics
Tata iQ by Forge
January 1, 2025 – Present
Python for Data Science
IBM Skills Build
January 1, 2024 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a proactive approach to learning and applying data science concepts. The diversity in projects (credit risk, property pricing) shows adaptability and a broad interest in different data domains. Involvement in a Data Science Club and volunteer work indicates a collaborative spirit and a willingness to contribute beyond academic requirements, suggesting a positive cultural fit for a team-oriented environment. However, the lack of professional experience means cultural fit is primarily inferred from academic and extracurricular activities.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a problem-solving mindset and an ability to translate complex data into actionable insights. Participation in the Data Science Club and NSS suggests teamwork and community involvement. The 'Job Simulation in Data Analytics' certification implies exposure to real-world analytical workflows and stakeholder communication, which are crucial for operational fit.