Data analyst

ABHISHEK KURHADE

Rahata ****************@*****.*** +91-766******* Linkedin Scaler My Portfolio

SKILLS

SQL, Tableau, Python, Machine Learning, SVM (Support Vector Machine), Statistical Modelling, MySQL, AWS, Excel, Git, Power BI, NumPy, SeaBorn, Google Colab, BigQuery, Docker, scikit-learn, Matplotlib, Pandas, GitHub, CI/CD PROJECTS

Target SQL

To optimize strategic decisions by analyzing 100K+ Target Brazil orders across customer behavior, logistics, and payment trends.

Conducted advanced SQL analysis in Big Query across multiple datasets—orders, deliveries, and customers—and built interactive Tableau dashboards to visualize KPIs, seasonal order peaks, and regional performance, enabling stakeholders to track delivery timelines, payment patterns, and business trends in real time. Identified seasonal order peaks revealing a 62.93% order value growth. Delivered actionable recommendations on customer service, regional strategy, and logistics planning NETFLIX: DATA EXPLORATION AND VISUALIZATION (PYTHON) To support Netflix’s content and launch strategy by exploring content trends across 8,800+ titles. Performed data wrangling and EDA by merging and un-nesting cast, genre, and country fields. Visualized genre popularity, optimal release weeks, and regional trends. Found week 27 (TV) and week 1 (movies) as ideal launch times. Revealed top-performing genres (International movies, Dramas, Comedies) and a 547-day lag between release and Netflix addition, influencing acquisition and marketing timing.

DELHIVERY: FEATURE ENGINEERING

Enhance Delivery’s logistics operations by ensuring data integrity, extracting meaningful features, and developing a framework for accurate demand forecasting.

Applied data cleaning, preprocessing, hypothesis testing, and outlier detection on logistics datasets. Engineered features from destination, source, and trip creation time, improving dataset reliability. Flagged high-delay corridors, and identified key states (MH, KA, TN, UP) for targeted improvement. Recommendations included hop delay reduction and regional route tuning, enabling data-driven operational LOANTAP

Predict borrower creditworthiness to minimize loan defaults and improve risk-based decision-making. Built a Logistic Regression model using 390K+ loan records; performed EDA, feature engineering, and SMOTE balancing to handle class imbalance and identify key risk drivers such as income, loan grade, term, interest rate, and debt-to-income ratio.

Achieved ~89% accuracy with 95% precision, enabling the business to reduce NPAs by tightening approvals for high-risk borrowers and optimize disbursal strategy toward creditworthy profiles. EDUCATION

BA

ACS college puntamba 2022

SCALER ACADEMY

Specialized in Data Science & Machine Learning

Pursuing Data Science & ML at Scaler Academy with expertise in SQL, Tableau, Excel, Python, EDA, Machine Learning. Experienced in applying data-driven solutions to real-world business problems through hands-on case studies.

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