You will get Tabular Regression Model for Revenue, Pricing, and Business Decisions
Project details
You will get a reliable regression model for revenue, pricing, or other business metrics, built with a strong focus on decision-making and real-world constraints, not just raw accuracy.
I specialize in machine learning for tabular data, where careful feature engineering, proper validation, and model choice matter more than complex black-box methods. My workflow emphasizes leakage-safe evaluation, clear metrics, and scenario analysis so you can understand how predictions change under different business assumptions.
Instead of delivering a single number, I provide interpretable insights into the drivers of your target variable and practical recommendations you can act on. The final output is reproducible, well-documented, and designed to integrate smoothly into existing analytics or pricing workflows.
This project is ideal for teams that want trustworthy predictions they can explain and use to support pricing, revenue, and strategic decisions.
I specialize in machine learning for tabular data, where careful feature engineering, proper validation, and model choice matter more than complex black-box methods. My workflow emphasizes leakage-safe evaluation, clear metrics, and scenario analysis so you can understand how predictions change under different business assumptions.
Instead of delivering a single number, I provide interpretable insights into the drivers of your target variable and practical recommendations you can act on. The final output is reproducible, well-documented, and designed to integrate smoothly into existing analytics or pricing workflows.
This project is ideal for teams that want trustworthy predictions they can explain and use to support pricing, revenue, and strategic decisions.
Machine Learning Tools
Keras, NumPy, pandas, Python, Python Scikit-Learn, PyTorch, scikit-learn, SciPy, XGBoostWhat's included
| Service Tiers |
Starter
$50
|
Standard
$150
|
Advanced
$600
|
|---|---|---|---|
| Delivery Time | 5 days | 8 days | 15 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 3 | 5 |
Number of Scenarios | 1 | 3 | 5 |
Number of Graphs/Charts | 5 | 10 | 15 |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | - | - | |
Source Code | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$100 - $200
Additional Scenario
(+ 2 Days)
+$50
Model Interpretability & Feature Importance
(+ 1 Day)
+$50Frequently asked questions
About Pablo
Data Scientist
Montevideo, Uruguay - 9:17 am 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 & target alignment
Review the dataset, validate target definition, check missing values/outliers, and confirm rules to avoid leakage (especially if there is a time component).
Feature engineering & baseline model
Build a baseline regression model and engineer key features (aggregates, ratios, interactions). Establish benchmark metrics (MAE/RMSE/R²).