Top Tech Jobs & Startup Jobs

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.

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.

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.

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.

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.

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.