Jobs at DataVisor

As a Senior Sales Engineer, you will engage with clients to align DataVisor's solutions with their fraud and compliance needs, conduct presentations, and drive technical integration discussions.

Lead and facilitate agile sprint and release processes across engineering teams: run sprint planning, track metrics, coordinate QA and bug fixes, control release scope and branching, run incident response and postmortems, manage cross-team projects, and report status to senior leadership.

Design and validate pre-built fraud detection models and cold-start scoring for payments and onboarding. Analyze large-scale consortium data to derive deployable features, test AI agent logic, and collaborate with Product, Engineering, and Strategy to productionize ML and LLM solutions with strong statistical rigor.

The role involves designing machine learning systems, optimizing real-time data processing, and building large-scale pipelines for fraud detection.

The Senior Account Manager is responsible for managing and growing relationships with strategic enterprise customers, focusing on upsell opportunities and customer success through engagement and collaboration with internal teams.

The Senior Software Engineer will design and build machine learning systems for fraud detection, optimize tools, and develop real-time distributed systems using big data technologies.

Provide fast-paced technical support for DataVisor clients via Zendesk, triage and monitor system health, collaborate with Engineering and Product on escalations, document issues in Jira, analyze recurring problems, and support customers on a Wednesday–Sunday schedule. Must be resident of Japan.

Lead and grow the Platform Engineering team to design, architect, and deliver a large-scale AI-driven fraud and risk decisioning platform. Set technical vision and roadmap, drive adoption of big data and real-time systems, collaborate with product and data science, enforce engineering rigor, and hire and develop senior engineering talent.

Manage a portfolio of customers as a trusted technical advisor for fraud and risk use cases. Oversee data integration and onboarding, troubleshoot platform performance, architect ML and rule-based solutions, lead deployments and business reviews, and coordinate cross-functionally to drive adoption and product improvements.

Design and build large-scale machine learning and real-time streaming systems to detect fraud using unsupervised, supervised, and deep learning; build pipelines using big data technologies and optimize distributed systems for real-time detection.

Lead technical and strategic engagements in fraud detection, data analysis, and risk strategy development using DataVisor's platform. Collaborate cross-functionally and manage client projects for improved fraud prevention and operational efficiency.

Serve as strategic partner to enterprise clients to drive ROI from an AI-powered fraud and AML SaaS platform. Lead onboarding, monitor detection performance, advise on ML and rule-engine strategies, coordinate with product and engineering, deliver business reviews, and educate customers on fraud/AML best practices to reduce risk and optimize operations.

Provide fast-paced technical support for DataVisor's fraud prevention SaaS platform (Wednesday–Sunday schedule). Triage and resolve customer tickets via Zendesk, monitor system health and alerts, collaborate with engineering for root-cause analysis, document findings in Jira, analyze recurring issues, and feed product team with usability and enhancement feedback.

Lead and scale Product Marketing for DataVisor's fraud and AML platform: set GTM strategy, positioning, launches, competitive intelligence, enablement, segmentation, metrics, and build a high-performing PMM team while partnering cross-functionally to drive adoption and revenue.

Serve as strategic Customer Success Manager for enterprise clients, driving ROI from fraud detection and AML platform use. Monitor detection performance, advise on ML and rule-engine tuning, coordinate with Product and Engineering, run business reviews, educate clients on best practices, and translate customer needs into product feedback to reduce fraud and streamline operations.

Serve as strategic partner and primary contact for enterprise clients, driving ROI from the fraud/AML SaaS platform. Advise on detection performance, ML-based models, rule engines, and best practices; coordinate with Product and Engineering; deliver business reviews, client education, and actionable feedback to reduce fraud and improve operations.

Serve as strategic partner to enterprise clients to drive ROI from fraud detection and AML solutions. Lead onboarding, monitor detection performance, advise on ML and rule-engine usage, coordinate with Product and Engineering, run QBRs, educate on best practices, and identify expansion and optimization opportunities.

As a Senior Technical Account Manager, you will manage client portfolios, provide technical guidance, oversee data integration, and ensure optimal platform usage for fraud detection.

The Software Engineering Manager will lead the Platform Engineering team, managing engineers while architecting an AI-based fraud detection platform utilizing big data technologies.

Develop machine learning systems to detect fraud in real-time, utilizing both supervised and unsupervised learning algorithms. Design scalable architecture and optimize data processing systems using big data technologies.