New grad Data Science engineer. Built Alma (AI study app on iOS), ML research on seizure prediction. Python, SQL, React

Mohammad Salem  • Peerlist

• Developed an interactive dashboard featuring multiple insightful charts based on a sample sales dataset. • Used geographic heatmap in tableau to present regional performance. • Created a time-series analysis chart that presents revenue trends and sales distribution.

Tableau Sales Analytics

• Cleaned and preprocessed data using Python (Pandas), then used seaborn for exploratory data analysis and visualization of tuition trends. • Created OLS Regression Model using statsmodels to predict tuition which achieved an R2 score of 0.94.

US Tuition Analysis & Modeling

• Cleaned and organized a database of sales and clients. Cleaning clientele data resulted in formatted addresses and contact info for marketing, as well as preprocessing for analysis and prediction. • Generated a geographical heat map of sales to determine good and poor performing areas in the market. Lead to 7+ marketing opportunities. • Gathered insights on sales trends via data visualization. Generated 7 insights on purchase patterns with 4 visuals. • Created an ML Model to predict the next purchase category using XGBoost and deployed it with Streamlit.

Signs of 2000 Sales Insights	      								  

• Created Linear Regression model using sklearn to predict walkability index. • Optimized performance through feature selection. • Predicted walkability index with a 0.92 R2 score.

Walking Difficulty Prediction ML Model       

• Extracted key metrics to reveal trends ( e.g. average project award per region, et al. ). • Developed visualizations to portray differences clearly to non-technical audiences. • Presented and translated findings in an easily digestible format, effectively communicating data-driven insights.