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Provide product and system support to clients, triage support requests, monitor system health, and troubleshoot issues. Collaborate with engineering and product teams to enhance services and document findings.

Manage and expand a portfolio of strategic enterprise accounts, driving adoption, renewals, upsell, and revenue growth. Act as trusted advisor to executive stakeholders, develop account plans, coordinate cross-functional teams, forecast opportunities, and lead contract negotiations to ensure long-term customer success.

As a Senior Strategic Financial Analyst, you'll oversee financial planning, KPI definition, model building, and system integrations while collaborating with finance and sales leadership to drive strategic initiatives.

The Senior Strategic Financial Analyst will enhance financial planning and reporting systems, support strategic decision-making, and integrate CRM with finance systems.

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.

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.

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.