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$
USD
I will build predictive models for business forecasting
Data Science Engineer: Finance, Stats and Teaching
Experienced Data Science Engineer with a robust background in statistics and finance. I excel in financial data analysis, predictive modeling, and project management, delivering actionable insights to...
About this Gig
I build custom predictive models that help businesses forecast outcomes, reduce risk, and make data-driven decisions.
With expertise in machine learning, statistical analysis, and financial modeling, I deliver accurate prediction systems tailored to your specific needs.
What I offer:
- Regression models for forecasting (sales, revenue, prices, demand)
- Classification models for risk assessment (churn, fraud, credit scoring)
- Time series analysis for trend prediction
- Complete data preprocessing and feature engineering
- Model optimization with hyperparameter tuning
- Deployment-ready pipelines for production use
Industries I work with:
Finance, e-commerce, healthcare, agriculture, sports analytics, and more.
What you get:
Trained machine learning model (Python)
Jupyter notebook with full documentation
Performance evaluation report (accuracy, ROC, confusion matrix)
Feature importance analysis
Clean, reusable code
I use Python, scikit-learn, XGBoost, pandas, and modern ML tools to build models that achieve 85-99% accuracy on real-world data.
Portfolio: stock price prediction (99.5%), fraud detection (96% AUC), churn models, drought forecasting.
Programming language:
Python
•
R
•
SQL
Frameworks:
Scikit-learn
•
Keras
•
PyTorch
•
Panda
Tools:
Jupyter Notebook
•
TensorFlow
•
Excel
•
MLflow
My Portfolio
FAQ
What data do you need from me to build the model?
I need a dataset in CSV, Excel, or database format with your historical data. For forecasting, include the target variable you want to predict and any relevant features (dates, categories, numerical values). I'll guide you on data requirements during our discussion.
What industries and use cases do you work with?
I work across multiple industries: finance (stock prediction, credit scoring), e-commerce (sales forecasting, customer churn), healthcare (risk assessment), agriculture (yield prediction), and sports analytics. If you have data and a prediction goal, I can build a model for it.
How accurate will my predictive model be?
Accuracy depends on data quality and complexity. My portfolio models achieve 85-99% accuracy. I provide detailed performance metrics (accuracy, ROC-AUC, confusion matrix) so you know exactly how well the model performs before deployment.
Do I get the source code and can I use it commercially?
Yes! All packages include full source code (Python notebook) with documentation. You own the code and model completely—use it commercially, modify it, or integrate it into your systems without restrictions.
