You will get a Regression Model and Predictive Churn Analysis Pipeline in Python
Project details
Don't Let Class Imbalance Hide Your Risk: Build Rigorous Predictive Models to Catch Churn Before It Happens
When predicting binary customer outcomes like churn, hitting a high baseline accuracy score is often a dangerous illusion. If 80% of your customer base naturally stays, a completely broken model that blindly guesses "retained" every time will still be 80% accurate—while missing 100% of the users who are actually walking out the door.
I specialize in constructing robust, multi-variable binomial logistic regression pipelines in Python using the structured PACE framework. I help businesses look past misleading baseline summaries, execute strategic multi-variable evaluations, expose critical recall deficits, and isolate the exact behavioral habits that decrease the log-odds of a customer churning.
When predicting binary customer outcomes like churn, hitting a high baseline accuracy score is often a dangerous illusion. If 80% of your customer base naturally stays, a completely broken model that blindly guesses "retained" every time will still be 80% accurate—while missing 100% of the users who are actually walking out the door.
I specialize in constructing robust, multi-variable binomial logistic regression pipelines in Python using the structured PACE framework. I help businesses look past misleading baseline summaries, execute strategic multi-variable evaluations, expose critical recall deficits, and isolate the exact behavioral habits that decrease the log-odds of a customer churning.
Data Tool
scikit-learnWhat's included
| Service Tiers |
Starter
$150
|
Standard
$350
|
Advanced
$575
|
|---|---|---|---|
| Delivery Time | 2 days | 4 days | 5 days |
Number of Revisions | 0 | 1 | 1 |
Number of Graphs/Charts | 0 | 3 | 3 |
Number of Scenarios | 1 | 1 | 2 |
Number of Model Variations | 0 | 1 | 3 |
Model Documentation | |||
Data Source Connectivity | |||
Model Validation/Testing | - |
Optional add-ons
You can add these on the next page.
Additional Revision
+$10
Additional Graph/Chart
(+ 1 Day)
+$10Frequently asked questions
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Selawik U.
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About Eldwin John
Data Scientist & Business Intelligence Analyst
San Pablo, Philippines - 11:47 am local time
Services include:
- Business Intelligence & Dashboarding (Tableau, Power BI)
- Advanced Analytics & Predictive Modeling (Python, R, SQL)
- Spend Analysis, Demand Forecasting & Data Cleaning
Steps for completing your project
After purchasing the project, send requirements so Eldwin John can start the project.
Delivery time starts when Eldwin John receives requirements from you.
Eldwin John works on your project following the steps below.
Revisions may occur after the delivery date.
Plan: Data Cleaning & Correlation Sweeping
I ingest your dataset, isolate target features, drop administrative identifiers, and map out a correlation heatmap to drop collinear variables exceeding absolute baseline thresholds.
Analyze & Construct: Outlier Mitigation & Feature Generation
I programmatically cap continuous outliers at the 95th percentile, convert categorical indicators into binary flags, and engineer custom operational behavioral metrics to capture user subgroups.