You will get Customer Segmentation & Clustering
Project details
You will get a clear and actionable customer segmentation, built using unsupervised machine learning to uncover meaningful patterns in your data.
I specialize in clustering and exploratory machine learning for structured data, where the goal is not just grouping customers, but creating segments that can be used for strategy, marketing, pricing, and product decisions. The process focuses on proper feature scaling, dimensionality reduction, and cluster validation to avoid arbitrary or misleading groupings.
Instead of delivering raw clusters, I translate them into interpretable segments with clear characteristics and practical recommendations. The result is a segmentation you can understand, explain, and actually use.
This project is ideal for customer analysis, personalization, pricing strategies, and targeting decisions.
I specialize in clustering and exploratory machine learning for structured data, where the goal is not just grouping customers, but creating segments that can be used for strategy, marketing, pricing, and product decisions. The process focuses on proper feature scaling, dimensionality reduction, and cluster validation to avoid arbitrary or misleading groupings.
Instead of delivering raw clusters, I translate them into interpretable segments with clear characteristics and practical recommendations. The result is a segmentation you can understand, explain, and actually use.
This project is ideal for customer analysis, personalization, pricing strategies, and targeting decisions.
Machine Learning Tools
NumPy, pandas, Python, Python Scikit-Learn, R, scikit-learn, SciPyWhat's included
| Service Tiers |
Starter
$50
|
Standard
$150
|
Advanced
$450
|
|---|---|---|---|
| Delivery Time | 5 days | 7 days | 11 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 2 | 4 |
Number of Scenarios | 1 | 2 | 4 |
Number of Graphs/Charts | 4 | 8 | 12 |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | - | - | |
Source Code | - |
Frequently asked questions
About Pablo
Data Scientist
Montevideo, Uruguay - 9:46 pm local time
I can help you with:
• Building and training classification, regression, or clustering models
• Designing full ML pipelines (data cleaning, feature engineering, evaluation)
• Computer Vision tasks such as detection, segmentation, or tracking
• Geospatial analysis using GeoPandas, QGIS, and satellite imagery
• NLP applications: text classification, summarization, and automation
• Data extraction, transformation, and analysis
Core technologies: Python, NumPy, Pandas, Scikit-Learn, PyTorch, TensorFlow, XGBoost, Optuna, GeoPandas, QGIS.
My approach is straightforward: understand the problem, design the most effective solution, and deliver clean, reproducible work.
Steps for completing your project
After purchasing the project, send requirements so Pablo can start the project.
Delivery time starts when Pablo receives requirements from you.
Pablo works on your project following the steps below.
Revisions may occur after the delivery date.
Data review & feature preparation
Clean data, scale features, remove leakage, and prepare inputs suitable for clustering.
Clustering & validation
Apply and compare clustering methods (e.g., k-means, hierarchical, density-based) and validate cluster stability and separation.