Intermediate Data Science| Anti-Fraud
Tasks
- Analyze user behavior patterns for new fraud prevention opportunities
- Build behavioral risk scoring algorithms
- Continuously improve model features
- Deploy models to production
- Design and run experiments and A/B tests
- Design blocking rules and automated decision strategies
- Detect promotional fraud consumer abuse payment fraud multi-accounting
- Develop dashboards for fraud KPIs
- Develop machine learning models for fraud prevention
- Monitor deployed models and fraud rules
Perks/Benefits
- Attendance bonus
- Casual office dress code
- Childcare subsidies
- Clube Ben partnership
- Days off
- Dental insurance
- Discounts on Ambev products
- Health insurance
- Language and training platforms
- Life insurance
- Meal allowance
- Medicines discounts
- Performance bonus
- Private pension plan
- Scholarship
- School materials assurance
- Transport allowance
- WellHub partnership
Skills/Tech-stack
A/B | A/B Testing | Anomaly Detection | B testing | Feature Engineering | LightGBM | Machine Learning | Model Monitoring | Model Validation | Python | SQL | Scikit-learn | Supervised Learning | Unsupervised Learning | XGBoost
Education
N/A
Roles
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