End-to-End Churn Machine Learning with Risk Scoring & DeploymentChristians Steven Zoe
End-to-End Churn Prediction System with Risk Scoring & Deployment
Customer churn is not just a model problem.
It is a revenue risk problem.
I design and build end-to-end churn machine learning systems that transform raw customer data into structured risk scoring outputs ready for business action.
This service goes beyond prediction accuracy.
It focuses on decision-making, revenue protection, and operational usability.
Business problem framing & KPI alignment
Define churn event & financial impact
Align KPIs with business objectives
Identify decision constraints
Data Assessment & Preparation
Data quality analysis
Missing value handling
Behavioral & transactional feature creation
Cohort-based indicators
Exploratory Data Analysis
Segment behavior insights
Risk pattern detection
Revenue-at-risk analysis
Model Development & Evaluation
Logistic Regression / XGBoost
Cross-validation
ROC-AUC, Precision-Recall
Profit-based threshold optimization
Risk Scoring System
Probability-based churn score (0–1)
Risk segmentation (Low / Medium / High)
Business-driven threshold calibration
Retention prioritization logic
Deployment-Ready API
FastAPI-based prediction endpoint
JSON scoring output
Model serialization (.pkl)
Integration-ready structure
Executive Business Report
Revenue impact estimation
Retention strategy recommendations
Clear explanation for non-technical stakeholders
What You Receive
Cleaned dataset
Reproducible ML pipeline
Serialized trained model
FastAPI scoring endpoint
Risk segmentation logic
Business report (PDF)
Documentation for integration
FAQs
Customer-level historical data including:
a. Transaction history
b. Engagement metrics
c. Subscription status
d. Customer attributes
If unsure, I can guide you.
SaaS, fintech, digital platforms, and subscription-based businesses.
A probability-based churn output converted into structured risk categories used for retention prioritization.
The system provides API-ready JSON output for CRM integration.
Full production deployment is available under custom scope.
The API structure is production-ready.
Cloud infrastructure setup can be scoped separately.
Up to 5 million rows under standard scope.
Larger datasets may require adjusted pricing.
Starting at$4,000
Duration4 weeks
Tags
FastAPI
Python
Business Intelligence
Churn Prediction
CRM Integration
Customer Retention
Machine Learning
Predictive Analytics
Risk Modeling
Service provided by
Christians Steven Zoe Kuta Selatan, Indonesia
End-to-End Churn Machine Learning with Risk Scoring & DeploymentChristians Steven Zoe
Starting at$4,000
Duration4 weeks
Tags
FastAPI
Python
Business Intelligence
Churn Prediction
CRM Integration
Customer Retention
Machine Learning
Predictive Analytics
Risk Modeling
End-to-End Churn Prediction System with Risk Scoring & Deployment
Customer churn is not just a model problem.
It is a revenue risk problem.
I design and build end-to-end churn machine learning systems that transform raw customer data into structured risk scoring outputs ready for business action.
This service goes beyond prediction accuracy.
It focuses on decision-making, revenue protection, and operational usability.
Business problem framing & KPI alignment
Define churn event & financial impact
Align KPIs with business objectives
Identify decision constraints
Data Assessment & Preparation
Data quality analysis
Missing value handling
Behavioral & transactional feature creation
Cohort-based indicators
Exploratory Data Analysis
Segment behavior insights
Risk pattern detection
Revenue-at-risk analysis
Model Development & Evaluation
Logistic Regression / XGBoost
Cross-validation
ROC-AUC, Precision-Recall
Profit-based threshold optimization
Risk Scoring System
Probability-based churn score (0–1)
Risk segmentation (Low / Medium / High)
Business-driven threshold calibration
Retention prioritization logic
Deployment-Ready API
FastAPI-based prediction endpoint
JSON scoring output
Model serialization (.pkl)
Integration-ready structure
Executive Business Report
Revenue impact estimation
Retention strategy recommendations
Clear explanation for non-technical stakeholders
What You Receive
Cleaned dataset
Reproducible ML pipeline
Serialized trained model
FastAPI scoring endpoint
Risk segmentation logic
Business report (PDF)
Documentation for integration
FAQs
Customer-level historical data including:
a. Transaction history
b. Engagement metrics
c. Subscription status
d. Customer attributes
If unsure, I can guide you.
SaaS, fintech, digital platforms, and subscription-based businesses.
A probability-based churn output converted into structured risk categories used for retention prioritization.
The system provides API-ready JSON output for CRM integration.
Full production deployment is available under custom scope.
The API structure is production-ready.
Cloud infrastructure setup can be scoped separately.
Up to 5 million rows under standard scope.
Larger datasets may require adjusted pricing.
$4,000