Mohammed Hussain

Data Scientist @Ruffalo Noel Levitz

Implemented ensemble method classifiers for Optimization of Calling Agent - Customer Matching Process thereby raising our fundraising revenue by 34% vs historical performance. Created a deep learning model in python using neural networks to determine the best time to attempt to call to a lead/prospect so that the matched prospect will be tied up by the calling platform to be called within the optimal window of time to result in a conversation based on any historical data, research code data and timezone information with 94% accuracy. Developed a supervised classification machine learning model using support vector machines (SVM), Scikit learn that could help predict whether a particular prospect/lead/alumni would be donating towards a fundraising marketing campaign or not. Created conversational AI chatbot using Facebook Blenderbot that can have authentic, informative conversations : applying for admission, financial aid info, alumni events, Giving Days etc in python thereby raising our crowdfunding sales by 31%. Created self- automated calling pool clusters containing prospective leads using K-means clustering algorithm. Leveraged Natural language processing to perform semantic text analysis in order to sense a particular prospect\'s emotion or attitude towards our marketing campaigns over their social media activity