Teams at Signifyd

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.

Build and deploy production machine learning models and fraud decisioning tools. Partner with business teams to identify performance gaps, automate repetitive work, run experiments, and optimize transaction-risk strategies. Write production and analytical Python code, use SQL and distributed data platforms such as Spark, Databricks, and GCP, and communicate findings to technical and business audiences. Participate in code reviews, peer collaboration, and an on-call weekend rotation approximately six times annually.