You will get Customer Churn Prediction Model | Machine Learning for Retention
Project details
You will get a customer churn prediction model that helps your business identify which customers are most likely to leave, so you can take action before it happens.
Using Python, SQL, and machine learning (scikit-learn, Pandas, NumPy), I will build a model that analyzes your historical customer data (transactions, demographics, activity, etc.) and delivers clear predictions, insights, and visual reports.
What sets this project apart:
🎯 Actionable retention strategy – focus your marketing on high-risk customers.
📊 Visual reports – see which factors influence churn the most.
⚡ Multiple package options – from a simple baseline model to a full automated pipeline with dashboards.
💡 Scalable approach – models that can be updated with new data as your business grows.
Whether you’re a SaaS company, e-commerce store, or service provider, this project gives you the tools to reduce churn, improve retention, and grow customer lifetime value.
Using Python, SQL, and machine learning (scikit-learn, Pandas, NumPy), I will build a model that analyzes your historical customer data (transactions, demographics, activity, etc.) and delivers clear predictions, insights, and visual reports.
What sets this project apart:
🎯 Actionable retention strategy – focus your marketing on high-risk customers.
📊 Visual reports – see which factors influence churn the most.
⚡ Multiple package options – from a simple baseline model to a full automated pipeline with dashboards.
💡 Scalable approach – models that can be updated with new data as your business grows.
Whether you’re a SaaS company, e-commerce store, or service provider, this project gives you the tools to reduce churn, improve retention, and grow customer lifetime value.
Machine Learning Tools
Apache Spark, Azure Machine Learning, BERT, ChatGPT, Deeplearning4j, GitHub Copilot, Google AutoML, Google Sheets, MLflow, NLTK, NumPy, Open Neural Network Exchange, OpenCV, pandas, Python, Python Scikit-Learn, PyTorch, scikit-learn, SciPy, SQL, TensorFlow, Tesseract OCR, XGBoostWhat's included
| Service Tiers |
Starter
$100
|
Standard
$250
|
Advanced
$500
|
|---|---|---|---|
| Delivery Time | 4 days | 6 days | 8 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 3 | |
Number of Scenarios | 1 | 2 | |
Number of Graphs/Charts | 2 | 4 | |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | |||
Source Code | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$30 - $150
Additional Model Variation
+$20
Model Documentation
+$10
Source Code
+$20Frequently asked questions
6 reviews
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BK
Bill K.
Feb 6, 2026
E-commerce Analytics + Looker Studio Expert (GA4 / CRO Specialist) for Analysis Coaching
Good when he shows up to work, which he hs challenges with. Always new reason.
SW
Shane W.
Jan 22, 2026
Job Post: AI-Assisted Web App for Christmas Light Layout Markup
The delivered MVP did not match the agreed scope. The project was clearly defined as generating an editable vector PDF with movable linework, including fascia light runs, power lines, and numbered segments based on provided examples.
The final output was a non editable PDF with flattened markup, plus a separate SVG containing only fascia shapes. The PDF did not include power lines, numbering, or line geometry consistent with the examples (lines were rendered as rectangular shapes rather than editable paths).
Delivery was provided as a zip file requiring local setup and running the app, which added friction for a non developer client. Communication was polite, but the core functional requirements had to be clarified multiple times and were ultimately not met.
The final output was a non editable PDF with flattened markup, plus a separate SVG containing only fascia shapes. The PDF did not include power lines, numbering, or line geometry consistent with the examples (lines were rendered as rectangular shapes rather than editable paths).
Delivery was provided as a zip file requiring local setup and running the app, which added friction for a non developer client. Communication was polite, but the core functional requirements had to be clarified multiple times and were ultimately not met.
JO
Jeff O.
Dec 26, 2025
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KA
Karim A.
Sep 19, 2025
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Rohan G.
Aug 18, 2025
Email Marketing Analytics Dashboard Developer - Mailchimp, GA4, Airtable Integration
About Ammar
Data Scientist | Python, SQL, Machine Learning & Dashboards
68%
Job Success
Khanewal, Pakistan - 6:10 am local time
I work with Python, SQL, Looker Studio, Google Sheets, GA4, APIs, and machine learning tools to build practical data systems, not just reports that look nice but do not get used.
Here’s what I can help with:
📊 Dashboards & Reporting
Looker Studio, Google Sheets, Excel, GA4, Google Ads, Search Console, CRM dashboards, KPI tracking, and automated reporting.
⚙️ Data Automation & ETL
Python scripts, API integrations, n8n/Zapier workflows, data cleaning pipelines, scheduled reports, and workflow automation.
🤖 Machine Learning & Predictive Modeling
Classification, regression, customer behavior analysis, churn prediction, forecasting, NLP, and model evaluation.
🧠 AI & LLM Workflows
AI summaries, document/data extraction, RAG pipelines, OpenAI/Claude API integrations, and insight generation from business data.
🧹 Data Cleaning & Structuring
Cleaning messy spreadsheets, joining data from multiple sources, fixing broken reports, and preparing reliable datasets for analysis.
My focus is simple: understand your business problem, clean up the data, build the right system, and make the output easy to use.
If you need someone who can handle both the technical side and the business logic behind the data, I’d be happy to help.
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Data Scientist | Python Developer | SQL | Machine Learning Engineer | Data Analyst | Predictive Modeling | Classification | Regression | Data Cleaning | Data Visualization | Dashboarding | Looker Studio | Google Data Studio | Business Intelligence (BI) | Excel Dashboards | Google Sheets | Automation Specialist | n8n | Zapier | Python Scripts | ETL | Pandas | NumPy | Scikit-learn | NLP | Sentiment Analysis | Time Series Forecasting | ARIMA | Prophet | Streamlit
Steps for completing your project
After purchasing the project, send requirements so Ammar can start the project.
Delivery time starts when Ammar receives requirements from you.
Ammar works on your project following the steps below.
Revisions may occur after the delivery date.
Data Review & Cleaning
I’ll inspect and clean your dataset to ensure it’s ready for analysis.
Feature Engineering & Model Training
I’ll create relevant features and train churn prediction models.