Taryn Fittro professional headshot

Taryn Fittro

Business Analytics Student & Aspiring Real Estate Analyst

About Me

I am a senior at the University of Iowa studying Business Analytics and Information Systems, graduating in May 2026. My academic path has been driven by a passion for turning raw data into actionable business decisions.

My career interests sit at the intersection of data analytics and real estate. I am drawn to how supply chain dynamics, market forecasting, and operations management shape the housing industry, and I am eager to bring an analytical lens to those challenges at firms in Chicago, Boston, or Silicon Valley.

Outside the classroom I focus on building real, end-to-end projects that reflect the kind of work I want to do — cleaning messy datasets, applying predictive models, and communicating findings clearly to stakeholders.

  • University University of Iowa
  • Major Business Analytics & Information Systems
  • Graduation May 2026
  • Focus Areas Real Estate Analytics, Forecasting, Operations

Skills

📊

Python

Data analysis and manipulation with pandas, including data cleaning, transformation, and exploratory analysis.

📈

Excel

Advanced spreadsheet modeling, pivot tables, and data summarization for business reporting and analysis.

🧹

Data Cleaning & Transformation

Preparing raw datasets for analysis — handling missing values, merging sources, and structuring data for modeling.

🌐

Orange

Building visual data mining workflows for classification, clustering, and predictive modeling tasks.

📚

Tableau

Currently developing skills in data visualization and dashboard design to communicate analytical findings effectively.

💬

Communication & Problem-Solving

Translating complex analytical results into clear, stakeholder-friendly insights and recommendations.

Projects

Python · Machine Learning

StreamFlix Movie Data Analysis

Analyzed a large movie dataset for a fictional streaming company to identify what factors drive viewer ratings. The project involved merging multiple data sources, cleaning and transforming the dataset, and building and comparing several predictive models.

  • Best model: Random Forest (R² = 0.477)
  • Tools: Python, pandas, scikit-learn
  • Key tasks: data merging, feature engineering, model evaluation
Orange · Classification

Data Mining Classification Project

Built and evaluated classification models using logistic regression and data mining workflows. Assessed model performance using a full suite of evaluation metrics to identify the strongest predictor configuration.

  • Techniques: logistic regression, confusion matrix analysis
  • Metrics: accuracy, precision, recall, F1 score
  • Tool: Orange data mining platform

Get in Touch

I am actively exploring entry-level analytics roles in real estate and related industries. If you think there could be a fit, I would love to connect.