I will build a python machine learning predictive model

Predicting outcomes churn, risk, demand gives businesses a real edge over just reacting to what already happened.

I'm a data analyst with an engineering background, and I build practical machine learning models using Python, Pandas, and Scikit-learn. My flagship project: a credit risk prediction model trained on 150,000 customer records using Random Forest, achieving 74% detection of late payments and an estimated $9.7M in savings for the business case.

I can build models for:

Classification (churn, risk, fraud detection)

Regression (sales forecasting, demand prediction)

Exploratory data analysis before modeling

What you get:

Clean, documented Python code (Jupyter Notebook or script)

Model evaluation (accuracy, precision, recall, confusion matrix)

Plain-language explanation of what the model found and why it matters

Optionally, a Power BI dashboard to visualize the results

I focus on models that are honest about their limitations and clear about business impact not just accuracy scores.

Send me your dataset and target variable, and let's see what's predictable in your data.