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Clara is Latin America's leading platform for corporate payments, serving 50,000+ businesses with corporate cards, bill pay, financing, and B2B payments. The company was named the region's fastest-growing by the Financial Times in 2025 and is backed by top-tier investors including Coatue, Kaszek, DST Global, and Goldman Sachs.
You will serve as a senior individual contributor fraud strategist reporting to the Head of Fraud, responsible for shaping and scaling Clara's global fraud detection strategy across all markets and fraud vectors. This role combines deep fraud expertise with analytical judgment and a builder mindset focused on AI and automation, balancing innovation with strong governance and risk controls.
Key responsibilities include:
- Define and own global fraud detection strategies, methodologies, and standards across fraud vectors, ensuring consistency and effectiveness across regions
- Drive evolution of Clara's fraud detection infrastructure, including rule engines, machine learning models, risk signals, and case management tools
- Lead the AI and automation roadmap for fraud detection, identifying opportunities to automate alert triage, investigations, and workflows using tools like N8N
- Explore and implement AI-powered detection capabilities including anomaly detection, behavioral analysis, and intelligent alerts
- Anticipate emerging fraud threats (AI-enabled fraud, synthetic identities, deepfakes) and develop mitigation strategies
- Establish model governance and risk management practices ensuring explainability, fairness, and appropriate human oversight
- Build mechanisms to share fraud intelligence across regions for faster pattern identification
- Monitor and challenge regional fraud detection performance using data platforms like Databricks and Metabase
- Partner with Fraud Operations, Risk, Product, Engineering, and Data Science teams
- Define automation and monitoring strategies enabling 24/7 fraud detection coverage
- Establish KPIs and performance frameworks measuring detection effectiveness, automation coverage, and platform reliability
You will work independently to influence cross-functional and regional stakeholders without direct management authority, translating complex fraud challenges into practical, scalable solutions.
REQUIREMENTS:
Must-haves:
- 7+ years of experience in Fraud Strategy, Fraud Prevention, Risk Analytics, Fraud Detection, or related functions, ideally within fintech, banking, payments, or financial services
- Strong expertise in fraud detection methodologies, rules-based strategies, risk signals, and transaction monitoring
- Experience designing, implementing, or optimizing fraud detection strategies and automated decisioning frameworks
- Strong understanding of machine learning, AI-driven fraud detection, and automation with ability to collaborate with technical teams
- Experience with fraud detection platforms, rule engines, case management systems, or risk decisioning tools
- Strong analytical skills with experience using SQL, Python, or similar tools to analyze fraud patterns and evaluate detection performance
- Experience defining and monitoring fraud detection KPIs (detection rates, false positives, automation coverage, model effectiveness)
- Understanding of model governance, explainability, risk controls, and human oversight in automated decision-making
- Proven ability to execute role-specific work and influence cross-functional and regional stakeholders without direct management authority
- Adaptability to fast-changing environments with strong ownership and problem-solving skills
- Experience or strong interest in using AI tools to automate workflows
Nice-to-haves:
- Experience designing or scaling fraud detection frameworks across multiple countries or business units, specifically within Latin American fintech or financial services
- Hands-on experience with AI-powered fraud detection, machine learning models, or automated investigation workflows
- Familiarity with GenAI, LLMs, agentic workflows, or automation platforms applied to fraud operations
- Experience with feature stores, model monitoring, anomaly detection, graph analytics, or advanced risk decisioning
- Knowledge of emerging threats such as synthetic identity fraud, deepfake-enabled attacks, and AI-driven fraud schemes
- Experience with model risk management, validation, fairness assessments, or AI governance
- Familiarity with card fraud, payment fraud, account takeover, identity fraud, or other financial fraud vectors
- Independent analytical skills using spreadsheets, SQL, or Python
