HealthFit Data Analysis - MongoDB Aggregations
Actionable health and business insights from siloed data using MongoDB aggregation pipelines. Includes baseline and optimized queries in both Python and JavaScript, plus clear README documentation.
Data Scientist • Skilled in Python, SQL, MongoDB, PostgreSQL, Business Analytics, and Financial Analysis
Actionable health and business insights from siloed data using MongoDB aggregation pipelines. Includes baseline and optimized queries in both Python and JavaScript, plus clear README documentation.
Financial ratio analysis and state-level aggregation in a reproducible Jupyter notebook. Covers debt-to-equity, descriptive stats, and exportable outputs with a clear workflow diagram.
Structured cleaning workflow for HR employee records: duplicates removal, missing-value imputation with flags, categorical standardization, derived salary validation, and outlier handling. Includes a polished README and a video walkthrough.
End-to-end data cleaning pipeline for U.S. Census datasets, handling messy CSV files, filling missing values, splitting demographics, and generating clear scatterplots and histograms to uncover population and income trends.
Simple demo that assigns race numbers and start times based on age and registration status.
Additional SQL, Python, and R analyses and dashboards will be linked here as they’re published.
I am a Data Scientist with experience across IT Management, Accounting, and Analytics. I focus on both Descriptive Analytics (historical data and what already happened) and Prescriptive Analytics (recommending future actions to improve outcomes). I’m currently pursuing a Master’s degree in Data Science.