Aryan Mudhole
Implementing machine learning for financial decision systems.
Master of Information Systems
Applied modeling • Regression logic • Business impact
About
I’m Aryan, and I’m glad you’re here. I began my journey with a Bachelor’s degree in Information Technology and early professional experience working with Power BI analytics and SAP MM in India.
Wanting to deepen my technical depth and gain global exposure, I moved to the United States to pursue a Master’s in Information Systems.
My long-term goal is to work at the intersection of data, machine learning, and finance—helping teams make informed, strategic decisions.
Washington DC Leadership Experience
I have tears while writing this. I never imagined that I would be gifted with so many experiences, lessons, and relationships in a single year.
As an international student, I never felt like I was away from home. Utah State University and the Jon M. Huntsman School of Business shaped me in ways I’ll carry for life.
“Ascend to higher ground and descend to higher ground.”
I approach data not just as numbers, but as a strategic asset that drives prediction, financial insight, and scalable decision-making.
How I Think About Data
📊 Data is currency
In today’s world, data drives growth. Businesses that understand their data make faster, smarter, and more profitable decisions.
📈 Prediction fuels scale
From forecasting demand to managing financial risk, predictive models turn historical data into a competitive advantage.
⚙️ Technology enables precision
Using advanced Python, machine learning, and fintech concepts, I build analytical systems designed for accuracy, clarity, and impact.
Projects
A selection of machine learning projects focused on real-world data and predictive modeling.
Financial Analytics
FinTech Loan Default Risk Modeling
Built classification models to predict loan default probability using cross-validation, feature engineering, and model optimization.
Machine Learning
Formula 1 Performance Analytics
Analyzed Formula 1 race performance data to uncover patterns in lap consistency, race strategy, and driver performance.
Machine Learning
Housing Price Prediction
Developed regression models to predict housing prices using structured datasets and feature engineering.
Model Evaluation & Insights
Evaluation metrics and interpretability analysis from my machine learning models. These visualizations demonstrate model performance, reliability, and feature impact.
Confusion Matrix
Visualizes the classification performance of the loan default prediction model. It highlights true positives, true negatives, false positives, and false negatives.
Accuracy: 91%
ROC Curve
Evaluates the model's ability to distinguish between borrowers who will default and those who will not.
AUC Score: 0.94
F1 Performance Insight
Analysis of the relationship between driver age and podium finishes using Formula 1 race data.
SHAP Summary Plot
Explains how individual features contribute to model predictions. SHAP values help interpret the impact of each variable on default risk.
Model Interpretability Analysis
Let's Connect
Explore my professional profile, code repositories, and resume.
Connect with me professionally and explore my experience.
View Profile →GitHub
Browse my repositories and explore my machine learning and analytics projects.
View Code →Resume
Data Analytics • Machine Learning • Python • SQL • Power BI
Experience building ML models, dashboards, and analytics tools using real-world datasets.