Melissa Dominguez Email and Phone Number

• Developing a Credit Risk Behavior Model for the Account Management team to accurately predict the likelihood of account default within a one-year timeframe.

• Used AWS technology to design, build, and implement large-scale analytical/statistical predictive models and queries.• Created a Tableau-based dataset and data visualization that permitted daily monitoring of loyalty and retention metrics.

• Rewrote legacy code using Python to change the logic for loyalty reporting and improve customer loyalty tracking accuracy by 20%.• Built automated cross-platform data pipelines, developed KPIs, dashboards, datasets, and data lakes using Spark SQL, Tableau, and Python.

• Achieved $500,000 savings during a workforce shortage by A/B testing delinquency letters, identifying the most effective approach for clients, and implementing risk logic using SQL and Python to determine recipients, enabling a headcount increase at operations centers.• Improved customer satisfaction metric from 73% to 85% by identifying through correlation analysis that agents with specific tenure needed additional training/coaching. Implemented findings led to enhanced scores.• Accelerated prescriptive data science using Tableau, SQL for dataset development, analyses, and visualizations. Led cross-functional reporting, devised data science solutions with SAS and Python for expanded Operations responsibilities, including project scoping.

• Improved customer recovery forecasting by 37% and reduced P&L losses in a temporary role through data-driven headcount management. Developed a capacity planning model to optimize staffing, ensuring adequate personnel during critical months and preventing shortages in key periods.• Attained 99% of monthly collection rate targets by collaborating with senior leadership to stabilize collections performance by creating a time-series forecasting model that had an error rate of 1% and mitigated losses in lower-performing months.

• Cut 80+ operational reports creation time by automating with SAS and SQL queries.• Achieved a 50% reduction in overtime for Operations' temporary analysts through enhanced report functionality and cost-effectiveness developing Tableau dashboards in collaboration with the team.

• Developed client-focused reporting for overseeing and analyzing performance analytics of Regional Advertising Campaigns.

• Working on projects to reduce waste and improve forecast.• Projects included: Promotional Forecasting of Strawberries and An Analysis of Cherry Picking (Used the Elements of Marketing Mix: The Four P's)• Performed statistical analysis on sales data.• Identifying and analyzing trends and seasonality in past sales data.• Independently researched sales data to complete multiple projects.• Implementing Key Performance Indicators (KPI's) to fresh and ambient categories.• Review and analyze trading of produce at market and sales class levels.• Collaborate with cross-functional teams to collect and validate data.• Design and develop strategies to analyze sales data with Excel.• Write complex SQL queries in Teradata to retrieve pertinent sales and waste data from large relational database.• Database mining and cleansing of data.• Assisted with forecast adjustments (uplifts) using in house software.• Presented analysis and findings to Supply Chain management and executives.

• Assist students at LBCC with designated learning assignments.• Tutored students in Mathematics (all levels).

• Responsible for recruiting students into program.• Provide students with assistance on financial aid and college applications.• Preparing students for college transitioning experience.• Assisted with workshops based on time management, financial aid application assistance, and housing applications.• Tutored students in Economics, Mathematics, Biology, and Chemistry.