BEN TELL

Data Science student specializing in accounting with proven skills in data analysis using SQL, Excel, Tableau, and Power BI. Proficient in machine learning techniques applied in Jupyter Labs, demonstrating ability to derive insights from complex datasets. Strong analytical capabilities combined with a solid foundation in financial principles. Committed to leveraging data-driven strategies to enhance decision-making processes.

• Global Fertility Analysis | Python, pandas, numpy, seaborn
  Cleaned and analyzed UN World Population data (1950–2021), revealing a ~50% decline in global fertility rates since 1950. Used bootstrapped linear regression and visualization techniques to uncover negative associations between fertility and female education levels and economic development, highlighting key factors driving fertility decline.
• Movie Genre Classification | Python, pandas, scikit-learn
  Built a k-Nearest Neighbors classifier using word-frequency features from 5,000+ screenplays, achieving 75% test-set accuracy in predicting movie genres. Applied feature selection to optimize performance and analyzed misclassification patterns to guide model improvement.
• Business Analytics & Tableau Dashboard | Tableau, Solver, PivotTables
  Built Excel models using Goal Seek, Solver, and advanced formulas (XLOOKUP, IF, IFS) to analyze revenue, expenses, and profits. Prepared and cleaned datasets, calculated turnaround times, and summarized key metrics with PivotTables and PivotCharts. Created interactive Tableau dashboards to visualize sales, profit, and customer trends, supporting data-driven decision making.