Data Science postgraduate with practical experience in machine learning, statistical analysis, and
end-to-end model development using Python. Worked on classification, segmentation, and
computer vision projects involving…
Data Science postgraduate with practical experience in machine learning, statistical analysis, and
end-to-end model development using Python. Worked on classification, segmentation, and
computer vision projects involving data collection, preprocessing, feature engineering, and model
evaluation. Comfortable working with real-world datasets and aligning analytical outcomes with
business objectives.
Cleaned and analyzed sales and payment data to build dashboards tracking weekday trends, payment modes, and manager-wise performance, enabling accurate operational reporting.
Prepared and analyzed customer transaction datasets to compute Recency, Frequency, and Monetary metrics, segmenting users into high-value and churn-risk groups and presenting insights through an interactive Power BI dashboard.
Processed large image-based datasets, applied data augmentation and labeling, and built classification models to convert raw satellite imagery into structured, analyzable land-use data.
Built a data collection and cleaning pipeline using APIs to compile rocket launch records, performed EDA and data validation, and generated analytical outputs to support mission risk and performance reporting.
Collected, cleaned, and prepared customer transaction data, performed feature engineering and validation, and analyzed factors influencing customer purchases. Built classification models and interpreted results to identify key behavioral and revenue drivers.
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