Asset & Wealth Management - Engineering - Fraud Detection & AI/ML Strategy - Vice President - Richardson
On-site · Richardson, Texas, United States
Job Summary
VP of Fraud Detection Engineering responsible for leading end-to-end AI/ML strategy to detect and mitigate fraud in real time across consumer deposit life cycle. Oversees design, training, and deployment of ML models (e.g., gradient boosted trees, transformers, graph neural networks), signal orchestration from behavioral biometrics to device fingerprinting and cross-platform transactional data, and low-latency inference pipelines for high-risk events. Focus areas include onboarding synthetic identities, securing money movement (ACH/wire/P2P), and defending against account takeovers and complex financial crimes. Leadership scope includes scalable data pipelines, centralized feature store, and rigorous model governance with back-testing and monitoring. Collaboration with CRO, product, and legal/compliance to align fraud roadmaps with regulatory requirements; mentorship and development of ML engineers, data scientists, and backend engineers in financial security; staying ahead of trends like GenAI-enabled deepfakes and automated bot attacks.
Required Qualifications
- Master’s in Computer Science, Statistics, Mathematics, or a related quantitative field
- 8+ years of software engineering or data science experience with at least 6 years in a senior leadership role within Fraud or Risk Tech
- ML expertise in anomaly detection and classification
- Proficiency in Python, PySpark, and cloud-native ML frameworks
- Domain knowledge of banking protocols (ACH, ISO 20022) and KYC/AML standards
Desired Qualifications
- Master’s in Computer Science, Statistics, Mathematics, or a related quantitative field
- 8+ years of experience in software engineering or data science, with at least 6 years in a senior leadership role within Fraud or Risk Tech
- Deep expertise in supervised and unsupervised learning, specifically for anomaly detection and classification in imbalanced datasets
- Proficiency in Python, PySpark, and modern ML frameworks. Experience with cloud-native AI services (AWS SageMaker, GCP Vertex AI)
- Strong understanding of banking protocols (ACH, ISO 20022) and identity verification standards (KYC/AML)
- Proven track record of reducing fraud loss while maintaining a seamless customer experience
- Ability to translate complex model performance metrics into business impact for executive leadership
- Executive-level leadership and mentorship capabilities
- Ability to collaborate with CRO, Product Leads, and Legal/Compliance teams
- Experience building scalable data pipelines and feature stores
- Experience with model governance, back-testing, A/B testing, and monitoring
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