CloudWalk - Operational Risk Analyst
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Requirements
• Strong knowledge of BACEN operational risk regulations (Res. BCB 265/2022, Res.4.557/2017, Circ.3.978/2020, and related standards). • Deep understanding of the payments ecosystem, including acquirer, sub-acquirer, and issuer operations. • Proven experience in fraud prevention and detection across the full fraud lifecycle — onboarding, monitoring, disputes, and recovery. • Expertise in developing and validating machine learning (ML) and AI models for fraud and risk management. • Programming and data analysis proficiency (Python, SQL, R) for scenario simulation, model validation, and automation. • Ability to design and deploy AI agents to automate risk management workflows. • Knowledge of IT and cybersecurity risk frameworks (NIST, COBIT, ISO 27001) and integration into operational risk practices. • Experience managing KRIs, RCSAs, and risk dashboards for management and regulatory reporting. • Analytical and critical thinker with the ability to translate data into actionable insights. • Hands-on and execution-oriented, capable of independently implementing and iterating solutions quickly. • Automation-driven mindset, always seeking ways to streamline processes using AI and technology. • Strong communication and storytelling, simplifying complex analyses for technical and non-technical audiences. • Collaborative team player, fostering strong partnerships across Data Science, Engineering, and Risk teams. • Attention to detail and accuracy, ensuring reliability in models, metrics, and reports. • Adaptable and proactive, thriving in a dynamic, data-intensive, and fast-growing fintech environment. • Ethical and transparent, ensuring compliance and integrity in all risk management activities.
Responsibilities
• Design, implement, and maintain the Operational Risk Management Framework in line with BACEN regulations. • Identify, assess, and monitor operational risk exposures, especially in fraud and IT-related processes. • Develop and validate AI/ML models for fraud detection, anomaly identification, and operational risk quantification. • Build and maintain AI agents to automate operational risk workflows — such as loss event tracking, KRI monitoring, and incident reporting. • Establish and monitor Key Risk Indicators (KRIs) and Risk and Control Self-Assessments (RCSAs) for ongoing risk tracking. • Collaborate with Data Science, Engineering, and Compliance teams to embed risk controls into product and process design. • Conduct scenario analyses and stress tests to evaluate operational resilience and inform management decisions. • Prepare clear and insightful risk reports and dashboards for senior management and regulatory audiences.
Benefits
• We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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