Aubrey Schrameck
Introduction
As a Data Science major at Northern Arizona University (graduating May 2026) with dual minors in Mathematics and Statistics, I am passionate about using data to uncover patterns, generate insights, and solve real-world problems.
My technical foundation includes programming languages such as Python, R, SQL, Java, and C, complemented by experience with SAP Analytics Cloud, Excel, QuickBooks, and Microsoft Office. Beyond academics, I have applied these skills in both research, developing deep learning models to analyze volcanic landforms through the NASA Space Grant Research Program, and in industry, streamlining financial data workflows and eliminating $162.5M in obsolete records during my internship with the City of Phoenix ERP Division.
Looking ahead, I aim to apply data science to drive positive impact in public and private sector industries, leveraging analytics to inform decisions, improve systems, and support communities through evidence-based strategies.
Education
Northern Arizona University | Expected May 2026
- Major: Data Science
- Minors: Mathematics & Statistics
- GPA: 3.9
- Scholarships: Lumberjack, Johanna Wheaton, and NAU Retirees Association
Technical Skills
- Languages: Python, R, SQL, Java, C
- Software: SAP Analytics Cloud, Excel, QuickBooks, Microsoft Office, Google Suite
- Other: Data cleaning, statistical modeling, visualization, machine learning, database management
Work Experience
NASA Space Grant Research Program | Undergraduate Researcher
Aug 2025 – Present
- Quantified volcanic cone and crater morphologies using USGS 3DEP data.
- Trained deep learning models in Python & R to classify eruption styles.
- Applied methods to volcanic landforms on Mars and the Moon.
- Research will culminate in a symposium presentation and a peer-reviewed publication.
City of Phoenix – Finance Department | Data Cleaning Intern (ERP Division)
May 2025 – Aug 2025
- Cleaned and reconciled large-scale financial datasets to support year-end closeouts.
- Eliminated $162.5M in obsolete shopping carts, improving reporting accuracy.
- Audited and validated purchase orders, contracts, and cost center hierarchies.
- Streamlined reporting workflows using SAP (ECC, SRM), Excel, and SAP Analytics Cloud.
Projects
Depression, Anxiety, and Stress Scale (DASS) Evaluation
- Analyzed survey responses from ~40,000 participants to assess response accuracy and reliability.
- Preprocessed data by isolating illness-specific questions and excluding non-diagnostic cases.
- Built visualizations to reveal mental health condition patterns.
- Tools: Python (Pandas, NumPy, Matplotlib)
World Happiness Score Analysis
- Analyzed Gallup World Poll data for 150+ countries, exploring links between happiness, GDP per capita, and life expectancy.
- Discovered strong positive correlations among happiness, wealth, and health metrics.
- Developed visualizations to illustrate global trends and insights.
- Tools: R (data cleaning, statistical analysis, visualization)
Currency Converter
- Collaborated on a Java-based currency converter with real-time exchange calculations.
- Designed and implemented a GUI for user-friendly interactions.
- Ensured robust exception handling and accuracy through comprehensive testing.
- Tools: Java (GUI development, backend logic)