Claudia Tun

- Using advanced data analytics techniques to assist DFCU with retention, acquisition, and personalized member experience efforts, in collaboration with senior technical and business leaders. - Working with stakeholders to understand the business problem, extracting relevant data for the business problem, exploring this data to identify meaningful insights, and using predictive analytics to predict future outcomes. - Using software such as Google Tag Manager (GTM) and Optimizely to track digital data that assists the Marketing team with tracking campaign performance and with digital based member segmentation efforts.

- Manipulated, transformed and analyzed data to answer business questions and collaborated with the team to find actionable insights for the stakeholders. - Built compelling data visualizations and dashboards using R, PowerBi and Excel to present the findings to leadership. - Built a predictive profitability model that accurately identified high-profit Arizona prospects in R for Desert Financial Credit Union, overseeing for the entire process from exploratory data analysis (EDA) to deployment.

- Performed data analysis using tools such as Microsoft Excel and R to report and track key metrics, enabling leadership to make informed decisions and enhance processes. - Created, designed, and built reports and presentations that include graphs, tables, and charts to translate data findings into visualizations that are easily understood. - Conducted research on assigned topics via external sources and summarize findings and provided insights

The MS program in data science, analytics and engineering enables students to receive an advanced education in high-demand data science and an engineering field in an integrated program. A core curriculum in probability and statistics, machine learning, and data engineering is complemented by concentration-specific courses to ensure breadth and depth in data science and a core engineering discipline.