Rebecca M. Rodriguez
Data Analyst Portfolio
About
I am a creative and data-driven professional with a unique blend of 3+ years of experience spanning business, neuroscience, and data analytics. Holding a Bachelor of Science in Biology, I bring a strong scientific foundation complemented by hands-on experience in laboratory neuroscience and business entrepreneurship. My academic background, coupled with data analyst certifications, demonstrates my commitment to continuous learning and adaptability in the ever-evolving field of data science.My passion lies in leveraging data-driven solutions to tackle complex problems, specifically in the realm of clinical and healthcare analytics. I am deeply motivated by the potential to improve clinical outcomes, enhance data integrity, and elevate the quality of patient care through advanced analytical techniques. My interdisciplinary background equips me with a holistic perspective, allowing me to bridge the gap between scientific inquiry and practical business applications.As I pivot into a career in data analytics, I am eager to apply my analytical skills, scientific rigor, and entrepreneurial mindset to drive meaningful insights in healthcare settings. My ability to translate complex data into actionable insights, combined with my enthusiasm for continuous learning, positions me as a valuable asset in the dynamic field of healthcare analytics.
Skills
Microsoft Excel/Google Sheets: Conditional Formatting, Data Visualizations, Mathematical Functions
Database Tools: MySQL WorkBench, PostgreSQL, Visual Studio Code, RStudio, Google BigQuery
Visualization Tools: Tableau, RStudio
Programming Languages: SQL(Window Functions, Regular Expressions, CTEs, JOINS, Subqueries, CASE Statements and Aggregate Functions), R (tidyverse, ggplot2), Python
Projects
HCAHPS Patient Satisfaction Survey: Data Cleansing & Insights Visualization
End Stage Renal Disease (ESRD)
Patient Census & Lab Metrics Visualization
Demographic Insights for Marketing & Sales Optimization in Tourism
Customer Churn
Trends & Insights
in Telecom
Education
The University of Texas at San Antonio
Bachelor of Science in Biology
HCAHPS Patient Satisfaction Survey: Data Cleaning & Visualization
Background:
The Hospital Value-Based Purchasing (VBP) Program is a value-based care program introduced in 2010 to incentivize quality patient care. Under this program, hospitals receive payment adjustments from The Centers for Medicare and Medicaid Services (CMS) based on the quality of care they deliver.The Hospital Consumer Assessment of Healthcare Providers and Systems survey (HCAHPS survey) is used to measure patients' perceptions of their hospital experiences. Hospitals submit patient responses to CMS for assessment. Each hospital's performance partially depends on the percentage of "top box" answers (patient survey scores = 9-10 or always) from the HCAHPS survey. The best performing hospitals receive a payment increase plus a bonus. Therefore, it is within the best interest of all hospitals to strive for the highest HCAHPS survey scores possible.
Utilized Excel to combine relevant data from raw CSV files and reformat non-numeric cells using Find and Replace.
Employed PostgreSQL to standardize, prepare and extract HCAHPS survey data from 3,000 U.S. hospitals to access patient care quality.
Reformatted dates and standardized provider CCN numbers using the TO_DATE, LPAD and CAST functions.
Prepared and identified essential data for exportation using WINDOW functions, ROW_NUMBER, CTEs and INNER JOINs.
Categorized hospitals and pertinent cohort survey answers in Tableau using calculated fields, bar graphs and delta spreads to identify hospitals providing the highest quality of patient care while highlighting areas in need of improvement.
End Stage Renal Disease (ESRD)
Patient Census & Lab Metrics Visualization
Comprehensive project details to be posted Fall 2025.
Demographic Insights for Marketing & Sales Optimization in Tourism
Business Scenario
A major tourism company, Company X, seeks to gain insights into their customer base, optimize their marketing strategies, improve their product offerings, design and pitch products more effectively.
Utilizing Excel, and Tableau, conducted exploratory data analysis (EDA) and customer segmentation on 4,888 customer travel records.
Employed bar graphs, pie-charts, histograms, and calculated fields to identify key customer demographics.
Discovered 60% of converted customers chose the basic travel package across all income demographics despite 4 other package options.
Created a PowerPoint presentation proposing the implementation of customer surveys to gain insights into customer preferences and drive sales growth among higher-income demographics.
Customer Churn Trends & Insights in Telecom
Business Scenario
A Telecom company has observed a significant number of customers leaving. This churn is affecting the company's revenue and market position.The company needs to identify key factors that contribute to customer churn and develop actionable insights to reduce churn rates and improve overall customer satisfaction.
Performed exploratory data analysis (EDA) on 7,043 telecom customers to identify key churn patterns.
Utilized Excel and Tableau to create pivot tables, bar graphs and filters to segment customers based on demographics.
Applied SUM and AVERAGE functions to reveal churned customers spent 53% less on monthly and 82% less on long-distance charges than retained customers.
Discovered churned customers were on average older in age and had shorter tenure durations.
Identified competition and customer dissatisfaction as the primary drivers of churn, providing actionable insights for retention strategies.
