Data Scientist Ii
Current◦ Developed a dynamic streamlit dashboard using Python and Snowflake for data storage, incorporating web scraping to collect data from various websites. Implemented TF-IDF Vectorization and Cosine Similarity for similarity analysis, enhancing results with simulated annealing optimization for interactive data analytics.◦ Achieved a projected annual revenue increase of $2.6M, saved 2600 labor hours per annum, and enhanced sales agility for swift competitor filter replacements.◦ Utilized ArcGIS for precise geocoding of sales addresses and implemented the k-d tree algorithm for efficient spatial indexing, enabling fast nearest neighbor searches in the geocoded dataset. Employed random forests, and K-means clustering for predictive analytics and customer segmentation, driving proactive customer engagement and enhancing sales revenue.◦ Led a major update for our company tool, switching from Node.js/JavaScript to Power Apps platform, This move cut down our maintenance costs by 30%. Implemented Power Automate to optimize information flow, enhancing operational efficiency. Achieved streamlined processes and notable cost savings.
