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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 Notable Capital, Coatue, Kaszek, and Goldman Sachs.
You will join as a Fraud Strategist Expert, a senior individual contributor role reporting to the Head of Fraud. This is a strategic position focused on shaping and scaling Clara's global fraud detection strategy across all markets and fraud vectors. You will combine deep fraud expertise, analytical judgment, and a builder mindset centered on AI and automation to balance 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, ML 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 strong model governance and risk management practices with focus on explainability, fairness, and 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
This role requires someone who can influence cross-functional and regional stakeholders without direct management authority, translate complex fraud challenges into scalable solutions, and thrive in fast-changing environments.
**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 including detection rates, false positives, automation coverage, and 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
