Jobs 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.

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.

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.

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.

Own DataVisor’s product marketing, PR, and analyst relations programs. Develop positioning, messaging, thought leadership, product assets, campaign materials, and executive communications while translating complex fraud, AML, AI, and SaaS technologies into customer-focused narratives. Collaborate across Product, Sales, Customer Success, Marketing, and leadership; manage agencies and analyst engagements; support launches and competitive intelligence; and use AI tools and agentic workflows to improve marketing productivity.

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.

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

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.

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.