• Developed a comprehensive Power BI Dashboard integrating a 94% accurate Random Forest Classification Algorithm, predicting student behaviors, and enabling proactive planning and resource allocation, resulting in achieving 100% of revenue potential.• Created a SARIMA model to forecast application numbers by demographics, aiding the marketing team in designing effective campaigns to attract and retain students, ensuring full revenue potential despite fluctuations.• Implemented tracking features in the dashboard for key metrics such as application numbers, cancellations providing critical data for strategic planning and targeted outreach, resulting in converting high-risk prospects into paying clients.• Analyzed revenue performance of various units identifying profitable and underperforming segments, diagnosing main reasons for losses, and suggesting data-driven improvements.• Developed a Power BI Dashboard to analyze revenue-generating vendors across campus dining halls, identifying the lowest performers. This insight enabled targeted improvements and strategic decisions to optimize vendor performance.• Developed a Power BI Dashboard using TextBlob and Python, reducing response time from one week to 2-3 days, identifying common student issues early, and increasing student retention by over 50%.• Engaged with clients to gather requirements and ensured the dashboards met their specific needs, leading to improved decision-making and optimized business outcomes, enhancing client satisfaction and retention.

• Conducted retention analysis to determine the session threshold where student discontinuation occurs, enabling targeted advising and increasing student enrollment by 40%.

• Attained a 100% pass rate among students, with an average grade benchmark of A- (94%).• Developed and instructed an "Introduction to Statistics" course for graduate-level Human Services and Addiction Counseling students, effectively engaging, and educating a cohort of 30 students.• Designed a robust syllabus for statistics, integrating contemporary tools and methodologies, while weaving in real-world applications specifically related to Social Services to bolster practical comprehension.• Employed a diverse teaching approach, combining traditional lectures, group activities, individual assignments, and discussions, resulting in consistent 100% class retention due to heightened student engagement and comprehension.• Provided prompt and constructive feedback on every assignment and homework for all 30 students, ensuring individual attention and guidance for optimal learning outcomes.• Garnered consistent acclaim from students for clear instruction and real-world applicability; notably surprised and surpassed supervisor's expectations with a rare 100% retention in a statistics class, reflecting students' genuine engagement and practical application of concepts.• Consistently liaised with the department's director, providing detailed updates on the progress of all 30 students, highlighting individual achievements and improvements throughout the course duration.

• Led a research initiative to conduct an in-depth research and analysis of student withdrawal patterns, identifying withdrawal timing and course completion percentage, and developed an action plan to improve course material, resulting in a 50% decrease in course dropout rates.• Conducted ANOVA test using R-Programming to model the impact of education background and experiences on grades achieved, ultimately identifying the best-fit model using the lowest AIC score.• Utilized Tukey's Honestly Significant Difference (Tukey's HSD) post hoc test to identify statistically significant differences between groups through pairwise comparisons.• Designed and deployed a VADER-based sentiment analyzer model in Python to analyze textual data from program assessment surveys and communicated the findings to the program director and provided actionable insights on key areas of improvement for the program, resulting in a 25% increase in overall program satisfaction.• Employed Qualtrics survey design to conduct a comprehensive program assessment, gather pertinent information regarding student demographics, education backgrounds, and prior work experiences.• Utilized Power Query within Microsoft PowerBI to effectively evaluate and transform column data types, as well as apply data shape transformations to enhance table structures. • Implemented an automated data-flow pipeline by integrating Microsoft Power Automate and Qualtrics, streamlining the process of collecting and storing data in a Microsoft Excel Spreadsheet.• Utilized findings to revamp select courses, making them more accessible to students and improving overall student retention rates.• Created detailed documentation of all analysis and report generation processes using R-Markdown, ensuring effective reproducibility by future student assistants. The documentation serves as a valuable resource for future projects and team members, streamlining the research process and reducing errors.

• Improved museum guest experience by analyzing visitor data and creating visualizations using ggplot2 to identify the busiest days and most active hours. Recommended extending museum hours based on findings, resulting in an 80% increase in the number of guests.• Utilized ggplot2 and Tidyverse to analyze and visualize demographic survey data, resulting in comprehensive reports on the museum's community. These reports contributed to the museum's successful accreditation process by providing valuable insights into the museum's visitors and their demographics, interests, and needs.