Advanced Fraud Detection System Development
Budget: €250 – €750 EUR
I'm looking for a skilled developer to enhance a fraud detection project based on the provided GitHub resources.
Key Tasks:
1. Update the existing XGBoost model to integrate time series classification techniques, improving model performance by considering the sequential nature of the data.
2. Develop an Enhanced Synthetic Data Generator that:
- Generates more realistic and variable synthetic data
- Is compatible with customer data, specifically bank transaction data.
3. Create a Fraud Detection System based on the provided GAN model that is trained on the Enhanced Synthetic Data.
Ideal Skills and Experience:
- Expertise in Machine Learning, particularly with XGBoost and Time Series Classification
- Strong experience in Synthetic Data Generation
- Proficiency in Generative Adversarial Networks (GANs)
- Familiarity with fraud detection methodologies and financial transaction data
Please provide a portfolio showcasing relevant projects and experience.
Key Tasks:
1. Update the existing XGBoost model to integrate time series classification techniques, improving model performance by considering the sequential nature of the data.
2. Develop an Enhanced Synthetic Data Generator that:
- Generates more realistic and variable synthetic data
- Is compatible with customer data, specifically bank transaction data.
3. Create a Fraud Detection System based on the provided GAN model that is trained on the Enhanced Synthetic Data.
Ideal Skills and Experience:
- Expertise in Machine Learning, particularly with XGBoost and Time Series Classification
- Strong experience in Synthetic Data Generation
- Proficiency in Generative Adversarial Networks (GANs)
- Familiarity with fraud detection methodologies and financial transaction data
Please provide a portfolio showcasing relevant projects and experience.