● Collaborated on 4 client projects within 10 months working with a government agency, a public school board, an educational testing company, and a financial literacy nonprofit organization. ● Developed automated process and predictive model for government client to identify individuals committing tax fraud, resulting in an improved process over 10 times faster with 87% accuracy.● Created K-Prototypes model using SQL and Python for nonprofit organization that identified most successful individuals, increasing precise marketing by 25%.● Identified, linked, cleaned, and merged multiple large data sources, of up to 8M-records, for the purpose of segmenting and classifying customers.● Organized projects as the Product Owner by leveraging Agile project management methodology and utilizing organizational tools such as Jira.

● Managed 8 team members to ensure best practices and compliance. ● Engaged with customers to help problem solve and address issues and complaints.● Reviewed department processes and created recommendations to supervisors based on customer feedback.

● Utilized Tableau to produce reports for senior leadership on vulnerability in employee retention and presented business recommendations to lower attrition rate by 13%.● Developed methodologies with Data Science team to predict employee attrition rate by using dataset containing close to 60 variables.● Built XGBoost model in Python and identified factors related to employee attrition.

● Using a dataset of over 100+ features, 2000+ schools over a 5-year period, pinpointed areas for improvement for school ranking based on data consisting of 100+ features. ● Devised a peer-focused analysis, gathered insights, and produced recommendations and a dashboard based on market analysis consisting of comparable schools. ● Executed a SWOT analysis aimed to uncover areas for improvements in rankings.