Teams at Signifyd

Lead end-to-end ML projects for fraud detection: develop, deploy, monitor, and iterate production models and experimentation frameworks. Improve model performance, build scalable ML pipelines, collaborate with Product/Engineering/Risk, and champion testing, documentation, and model-monitoring best practices to ensure robust, high-impact solutions.

Leads and develops an engineering team building, deploying, and operating machine-learning models and services for fraud prevention. Owns roadmap delivery, technical decisions, reliability, testing, monitoring, and stakeholder communication. Partners with data scientists, ML engineers, product, risk, and engineering teams. Drives responsible AI-tool adoption, recruits and coaches engineers, manages priorities, and ensures scalable, high-quality production systems.

Build and manage relationships with prospective and existing financial services partners, present tailored platform solutions, and represent Signifyd at industry and client events. Translate business needs into technical requirements and coordinate Product, Engineering, Legal, Sales, and partnerships teams. Manage client engagements, align internal milestones with external commitments, communicate roadmap timelines, shepherd contracts, identify risks, and drive resolution. Develop expertise in payments, e-commerce, fraud prevention, and the Signifyd platform.