I have completed Bsc in statistics and currently I am pursuing Msc in data science. I have hands on data analyst internship experience.
Conducted comprehensive sales analysis for a garment wholesaler using seven years of transaction data to derive insights on revenue, seasonality, and customer behavior.
Performed data preprocessing and feature engineering in Python, cleaning 19,775 records and creating time-based and discount-related features for analysis and modeling.
Built and evaluated machine learning models (Linear Regression, Random Forest, Gradient Boosting) to predict sales amounts and assess the impact of discounts and time factors.
Applied K-Means clustering to segment 728 customers into behavior-based groups and value tiers (Bronze, Silver, Gold, Platinum) for targeted retention and growth strategies.
Developed clear visualizations and dashboards (trends, distributions, customer segments, tax breakdown, discount impact) to communicate actionable business insights to stakeholders.
Conducted comprehensive sales analysis for a garment wholesaler using seven years of transaction data to derive insights on revenue, seasonality, and customer behavior.Performed data preprocessing and feature engineering in Python, cleaning 19,775 records and creating time-based and discount-related features for analysis and modeling.Built and evaluated machine learning models (Linear Regression, Random Forest, Gradient Boosting) to predict sales amounts and assess the impact of discounts and time factors.Applied K-Means clustering to segment 728 customers into behavior-based groups and value tiers (Bronze, Silver, Gold, Platinum) for targeted retention and growth strategies.Developed clear visualizations and dashboards (trends, distributions, customer segments, tax breakdown, discount impact) to communicate actionable business insights to stakeholders.Skills: Python, Machine Learning, Data Analysis, Customer Segmentation, Data Visualization (Matplotlib/Seaborn), Excel
Developed a Smart Demand Forecasting solution for perishable retail to reduce waste and maximize profit for local fruit and vegetable sellers.
Performed end-to-end data preprocessing, including data cleaning, handling missing values/outliers, and feature engineering for time-series demand patterns.
Conducted exploratory data analysis to identify sales trends, seasonality, and product-wise demand behavior to inform model design.
Built and evaluated machine learning-based demand forecasting models using Python and SQL to optimize inventory decisions.
Designed an interpretable Power BI dashboard to visualize forecast VS actual demand, waste, and profit, enabling data-driven decisions for shop owners.
I developed Smart Demand Forecasting for perishable retail with the goals of less waste and maximum profit for the local fruit and vegetable sellers. My work was over data preprocessing, analysis, modeling, and building an interpretable Power BI dashboard - Pytho, Sql, Machine Learning, Power Bi
Contributed as an AI/ML intern in developing AI-based smart glasses for people with visual impairments, focused on enhancing accessibility and independence among users.
Implemented real-time object detection using Python and YOLO to help users identify obstacles in their surroundings.
Integrated OCR and speech output to read printed materials aloud, enabling users to access text from documents, boards, and signs.
Developed scalable backend components and assistive AI features to support reliable, low-latency processing for real-time user assistance.
Utilized Python and machine learning techniques to design, test, and refine AI models tailored to assistive technology use cases.
Contributed as a backend intern in creating AI-based smart glasses for people with visual impairments. Developed using Python, YOLO for object detection in real-time, speech, and OCR for facilitating the ability to detect obstacles and read printed materials. Developed scalable backend systems and incorporated assistive AI technologies for expanding the level of accessibility and independence among users - Pytho, AI&ML, Machine Learning
Created an end-to-end cricket data analysis project using SQL and Python that cleansed, explored, and modeled player performance using machine learning algorithms. Created an interactive dashboard presenting key performance indicators visually, facilitating data-driven player analysis and critical decisions -Python, Machinne Learning, Sql, Power Bi
Led university-level water quality research project: collected & analysed multi-period water sample data from multiple MSU departments; ran statistical tests, and connected real data findings with student perception results.
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