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Fiverr Pro
English
$
USD
I will build predictive machine learning models for credit risk and fraud
I’m a passionate student specializing in quant finance, data science, and machine learning. I’ve built personal projects around algorithmic trading, financial modeling, and predictive analytics using ...
About this Gig
Stop losing revenue to fraud and defaulting customers.
If you run a fintech startup, lending platform, or e-commerce business, traditional rule-based risk systems are no longer enough. You need models that learn from your data to predict risk before it happens.
I build custom predictive Machine Learning models tailored to your financial data.
As a Computer Science Engineer with a strong Quant and AI/ML background, I don't just run basic scripts. I clean messy tabular data, engineer features, and train robust statistical models that give you actionable risk scores.
What I Can Build For You:
- Fraud Detection Models: Identify anomalous transactions accurately.
- Alternative Credit Scoring: Predict loan default risk using transaction history or user behavior.
- Customer Churn: Forecast which high-value clients are likely to drop off.
My Tech Stack:
- Python, Pandas, NumPy
- Scikit-Learn, XGBoost, Random Forest
- Jupyter Notebooks & FastAPI
Note: I maintain strict data confidentiality. Your historical business data is safe.
Please message me before placing an order to discuss your dataset!
Programming language:
Python
•
R
FAQ
Q: Is my company's data safe with you?
A: Absolutely. I adhere to strict confidentiality. Furthermore, I highly recommend that you anonymize or drop any Personally Identifiable Information (PII) like names, emails, or Social Security Numbers before sending the dataset.
Q: How much data do you need to train a good predictive model?
A: Machine learning thrives on data. Ideally, you should provide a dataset with at least a few thousand rows (historical transactions, past loans, etc.) to get reliable predictions. If you are unsure if your dataset is large enough or clean enough, send me a message, and I can take a look before.
Q: Can you guarantee 100% accuracy on fraud detection or credit risk?
A: No professional Data Scientist will ever guarantee 100% accuracy. A model that claims 100% accuracy is usually "overfitted" and will fail in the real world. Instead, I focus on maximizing metrics that matter to your business, such as Precision and Recall.
Q: What exactly will you deliver at the end of the project?
A: For the Standard tier, you receive a fully commented Jupyter Notebook with all Python code, data cleaning steps, model training, and performance graphs. For the Premium tier, you also receive a FastAPI Python script to easily integrate the model into your live app.
Q: Do I need to choose the algorithm?
A: Not at all! Just provide the historical data and tell me what you want to predict. I will test multiple algorithms (like XGBoost or Random Forest) and select the best performer for your specific use case.
