About Gina Aulabaugh

Applied Data Analyst · Predictive Modeling · Data Quality & Governance

Turning messy systems into decision-ready insight

I’m an applied data analyst focused on translating complex analytics into clear, decision-ready insight. I build and evaluate models, structure and clean data, and validate results with an emphasis on measurable business impact—not just statistical significance.

My work centers on predictive modeling, data quality assessment, and building reproducible analytical workflows. I use analytics to solve operational problems, especially in customer experience, retention, and performance optimization.

Before formalizing my analytics portfolio, I spent over a decade in high-volume, high-stakes customer environments. That experience gives me firsthand understanding of how metrics influence behavior, how incentives shape outcomes, and how reporting systems can drift from operational reality.

How I Work With Data

I work with data using a structured, decision-centered approach. I start by clarifying the business question, validating what the data can (and can’t) support, and choosing methods that fit the context—exploratory analysis, regression/classification, or feature engineering.

I treat data as a product of real systems—people, incentives, tools, and processes. When results look “off,” it’s often not the analysis that’s wrong, but the assumptions, definitions, or reward structures behind it. My goal is insight that holds up in real-world decisions—not just a cleaner dashboard.

Skills & Tools

Applied Analytics

• Explainable Analytics & Decision Support
• Hypothesis-Driven Analysis
• Predictive Modeling (Regression & Classification)

Data Preparation & Quality

• Data Cleaning & Wrangling
• Feature Engineering
• Data Quality Assessment
• Reproducible Analytical Workflows

Frameworks & Thinking

• CRISP-DM
• Systems Thinking
• Decision-Centered Analysis
• Ethical & Responsible Data Use

Tools & Technologies

• Python (pandas, numpy, matplotlib)
• SQL
• Jupyter Notebook / Google Colab
• Git / GitHub
• RapidMiner

Extended Bio

I build decision-ready analytics that hold up in real operations—predictive modeling, data quality checks, and reproducible workflows that turn noisy data into usable outputs.

Before formalizing PixelKraze, I spent over a decade in high-volume, high-stakes customer environments where accuracy, clarity, and trust matter. That background keeps my work outcome-focused and practical about metrics, incentives, and how reporting can drift from reality.

PixelKraze is where I publish that work—a portfolio of applied analytics projects, audit-ready artifacts (receipts, validation checks, run logs), and actionable outputs.

Quick facts

Location:

Ringgold, GA

Focus areas:

CX, retention/churn, ops, data quality

Open to:

projects, feedback, client work

View Resume

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