Teams at DataVisor

Build and operate production-grade AI, data, and distributed systems for fraud intelligence. Responsibilities include real-time data pipelines, high-throughput architecture, LLM-powered agentic workflows, AI tooling, rule and label automation, ML pipeline productionization, privacy safeguards, and cross-functional collaboration. The role requires strong Python engineering, distributed systems, cloud infrastructure, big data technologies, and machine learning fundamentals.

Manage and optimize GTM business systems and operational processes across Marketing, Sales, and Customer Success. Support HubSpot, CRM, marketing automation, integrations, data flows, and workflow automation. Build dashboards and executive reporting, analyze operational performance, improve data quality, and identify process efficiencies. Serve as a cross-functional resource for systems, reporting, and operational issues while using AI to enhance productivity and decision-making.

Develop and deploy machine learning models for fraud detection and risk assessment. Analyze large transactional datasets using exploratory analysis, Python, and data science libraries to uncover anomalies and patterns. Collaborate with engineering and business teams to integrate models into production, monitor performance, and improve algorithms. The role also involves researching emerging fraud detection and AI techniques.