Key skills
PythonSQLAIRemote Work
About this role
Role Overview
- Secure Onboarding: Configure and optimize rules to mitigate risks during customer onboarding (KYC/KYP), using tools such as identity validation, device fingerprinting, and credit bureaus.
- Decision Engine Management: Create, tune, and monitor antifraud rules in platforms like ClearSale, Credify and internal systems.
- Transactional Fraud Monitoring: Detect suspicious patterns and act on alerts. Examples:
- Batch purchases
- Automated attacks (bots)
- Account takeovers
- Multiple transactions to the same beneficiary
- Repeated card transactions from the same geolocation
- Monitoring of Suspicious Transactions (AML): Identify atypical behaviors (movements inconsistent with profile, smurfing, circularity of funds, etc.) and handle alerts.
- Chargeback Analysis: Monitor dispute rates, identify root causes (fraud, friendly fraud or operational error) and propose improvements and corrective actions.
- Conversion Optimization: Balance security and user experience, reducing false positives without increasing risk.
- Regulatory Reporting: Support the preparation of communications to COAF (Financial Intelligence Unit), when applicable.
- Regulatory Compliance: Ensure adherence to rules from the Central Bank of Brazil and internal policies.
- Conduct deep-dive analyses to identify vulnerabilities and new attack patterns.
- Propose improvements to flows, products and journeys to reduce risk.
- Collaborate with Product, Technology and Business teams to continuously evolve controls.
- Monitor key indicators (KPIs) such as fraud attempts, approvals, false positives and alerts.
Requirements
- Payment Methods: Domain knowledge of card processing flows (authorization, capture, settlement) and digital payment methods (Pix, boleto), including analysis of failures and risks in each process.
- Fraud Prevention: Practical experience with decision engines, rule creation and tuning, and transactional analysis.
- AML/CTF: Experience with KYC/KYB processes, transactional monitoring and identification of money laundering typologies.
- Bureaus and Data: Use of credit bureaus (Procob, Assertiva or similar) for risk assessment and decision-making.
- Regulatory: Knowledge of Central Bank of Brazil regulations and their application in day-to-day operations.
- Experience implementing or tuning antifraud engines.
- Experience in financial institutions, fintechs or acquirers.
- Experience with AML/CTF frameworks.
- Experience with graph analysis or transaction network analysis to detect suspicious patterns.
- Analytical Languages: Python and SQL.
- Ability to manipulate and analyze data, interpret metrics and generate insights (knowledge of SQL and Python desirable).
- Experience using AI tools for data analysis, pattern identification and decision support, as well as automation of operational routines.
Tech Stack
- Python
- SQL
Benefits
- Remote work (Home Office);
- Home office allowance;
- Meal/food voucher (Pluxee);
- Medical and dental plans (SulAmérica);
- Digital hospital services (Conexa);
- Life insurance (Prudential);
- Childcare assistance for children under five (5) years old;
- Wellhub (Gympass);
- Partnerships with Open English and ESALQ;