I will build machine learning and statistical predictive models in python
About this Gig
Have data and a question, but no model to answer it? I build predictive models that are accurate, explainable and ready to use.
I'm an Electronic Engineer completing a Master's in Data Science with AI, with years of experience working with real industrial data from sensors, test systems and production lines. I choose between classical statistics and modern machine learning based on what your data actually needs.
What I can build:
- Classification: churn, fraud, defect or failure prediction
- Regression: sales, prices, demand, quality metrics
- Time series forecasting: ARIMA/SARIMA and ML-based
- Statistical analysis: hypothesis testing, regression, significance
- ML: Random Forest, XGBoost, LightGBM, neural networks, clustering
What you get:
- Clean, documented Python code (Jupyter notebook)
- Honest evaluation with proper validation, tracked in MLflow
- Plain-language explanation of what drives predictions
- A trained model ready for new data
Tools: Python, pandas, scikit-learn, statsmodels, XGBoost, LightGBM, PyTorch, MLflow.
Not sure which package fits? Message me before ordering and I'll tell you honestly what's achievable.
Programming language:
Python
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R
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SQL
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NoSQL
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MLflow
FAQ
Do you sign NDAs?
Yes. I handle your data confidentially and can sign an NDA before you share it.
My data is messy. Can you still help?
Yes. Standard and Premium include data cleaning. If cleaning is extensive, I’ll let you know before starting.
Statistical model or machine learning: which is better?
It depends on your data. Statistical models are transparent and work well with smaller datasets, while ML often wins on larger, complex ones. I compare both and explain the tradeoff.
Can you guarantee a specific accuracy?
Not before seeing the data. I guarantee a rigorous process and a clear explanation of what your data can and can’t predict.

