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Director, FSI Predictive Technology

NVIDIA· Mgmt, Sys SW
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Santa Clara, CA$320k - $488.8kfull-timePosted 4w ago

About the role

Technical Fraud Director responsible for defining and guiding the technical direction for scalable fraud technology and platforms, combining rules, machine learning, anomaly detection, graph analytics, and risk scoring to build production-grade fraud detection, prevention, investigation, and decisioning systems.

Responsibilities

  • Lead the technical strategy, architecture, and roadmap for fraud technology built to scale and support customers in building, customizing, and operating fraud detection, prevention, investigation, and decisioning systems.
  • Design reusable detection approaches that combine rules, machine learning, anomaly detection, behavioral analytics, graph analytics, entity resolution, and risk scoring.
  • Partner with Data Science, ML Engineering, Product, and Customer Engineering teams to develop, evaluate, deploy, and continuously improve fraud detection capabilities for customer use cases.
  • Identify, prioritize, and integrate fraud signals across transactional, identity, account, device, network, application, behavioral, and operational data.
  • Establish frameworks for rapidly translating newly discovered fraud patterns into production rules, signals, models, and detection workflows that can be adopted across customer environments.
  • Define and monitor detection effectiveness using metrics such as precision, recall, false-positive rates, detection coverage, alert quality, latency, and business impact.
  • Lead technical root-cause analysis when fraudulent activity bypasses existing controls and drive improvements to detection logic, data coverage, and system resilience.
  • Build reusable detection infrastructure, services, APIs, reference architectures, and frameworks that support multiple products, fraud types, customer environments, and business use cases.
  • Evaluate emerging technologies and determine where AI, machine learning, graph analytics, automation, and analyst-assist tooling can improve fraud detection and response.
  • Lead technical build and architecture reviews, driving alignment across Development, Data Science, Security, Risk, Product, Customer Engineering, and Service Delivery collaborators.

Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related technical field, or equivalent experience.
  • 15+ years of progressive experience in software engineering or a related technical discipline, including 6+ years of experience leading and managing complex, cross-functional engineering organizations and delivering high-impact technical products or platforms.
  • Deep expertise in software engineering, fraud technology, risk systems, security engineering, machine learning, data science, or data engineering.
  • Significant experience designing, building, or operating large-scale fraud, abuse, risk, security, detection, or machine learning systems.
  • Experience developing platforms, products, APIs, services, or technical frameworks adopted by internal or external customers to build production systems.
  • Strong understanding of detection methodologies including rules-based, statistical, behavioral, anomaly-based, graph-based, and machine-learning approaches.
  • Experience designing real-time, high-volume, distributed, or event-driven data processing systems.
  • Experience with data pipelines, feature engineering, model inference, production ML systems, or decisioning platforms.
  • Demonstrated ability to identify meaningful signals within large and complex datasets and translate them into actionable detection capabilities.
  • Experience defining metrics and using data to evaluate and improve detection-system effectiveness.
  • Strong systems-thinking skills and the ability to turn ambiguous fraud patterns into clear technical requirements and scalable solutions.
  • Demonstrated experience leading complex technical initiatives across multiple engineering, data, risk, product, and customer-facing teams.

Skills

Required:Fraud technology strategy and architectureDetection methodologiesData integration and signals

Benefits

  • equity
  • comprehensive benefits package (benefits link provided in description)
Last updated Sep 25, 2026. Interested? Apply on the company site.

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