
501 - 1000 Mitarbeiter
Gegründet 2012
🤖 Künstliche Intelligenz
🔐 Sicherheit
💸 Finanzen
💰 €450.000.000 Series E im 2021-11
Artificial Intelligence • Security • Finance
Socure ist ein führender Anbieter von KI-gestützten Lösungen zur Identitätsverifizierung und Betrugsprävention. Ihre Plattform, bekannt als RiskOS™, ermöglicht es Organisationen, vertrauenswürdige Entscheidungen zu Identität und Risiko zu treffen, was ein nahtloses Onboarding und Management von Kunden über verschiedene Kontaktpunkte hinweg ermöglicht. Mit Echtzeit-, präzisen Identitätsprüfungen in über 190 Ländern hilft Socure, Identitätsbetrug zu bekämpfen, während es die Compliance sicherstellt und das Kundenerlebnis verbessert.
🕒 vor 2 Monaten
🇺🇸 Vereinigte Staaten – Remote
💵 $170.000 - $205.000 / Jahr
⏰ Vollzeit
🟠 Senior
✅ Produktmanager
🦅 H1B-Visum-Sponsor
🗣️🇺🇸🇬🇧 Englisch erforderlich
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501 - 1000 Mitarbeiter
Gegründet 2012
🤖 Künstliche Intelligenz
🔐 Sicherheit
💸 Finanzen
💰 €450.000.000 Series E im 2021-11
Artificial Intelligence • Security • Finance
Socure ist ein führender Anbieter von KI-gestützten Lösungen zur Identitätsverifizierung und Betrugsprävention. Ihre Plattform, bekannt als RiskOS™, ermöglicht es Organisationen, vertrauenswürdige Entscheidungen zu Identität und Risiko zu treffen, was ein nahtloses Onboarding und Management von Kunden über verschiedene Kontaktpunkte hinweg ermöglicht. Mit Echtzeit-, präzisen Identitätsprüfungen in über 190 Ländern hilft Socure, Identitätsbetrug zu bekämpfen, während es die Compliance sicherstellt und das Kundenerlebnis verbessert.
• Own the roadmap and execution for DocV’s forensic engine, including detection of document fraud, injection attacks, and AI-generated content. • Support efforts to scale DocV adoption globally, including in the public sector, financial services, and emerging markets. • Partner with Data Science to define, evaluate, and improve model performance across key fraud vectors. • Identify gaps in detection coverage and drive new signal development across image, video, and device layers. • Design and evolve decisioning frameworks that translate model outputs into actionable outcomes. • Build scalable, configurable logic that supports diverse customer risk profiles and use cases. • Balance fraud detection performance with user experience and conversion impact. • Work closely with high-value customers to understand fraud patterns, edge cases, and operational needs. • Translate customer feedback into product improvements and prioritization decisions. • Support complex customer implementations and act as a subject matter expert in DocV decisioning. • Collaborate with Engineering and Data Science to translate product requirements into technical execution. • Partner with the Fraud Investigation team, Customer Success, and Sales to align on product behavior and outcomes. • Drive alignment on tradeoffs between detection accuracy, false positives, and business impact. • Use SQL and analytics tools to evaluate model performance, decisioning outcomes, and conversion impact. • Define and track key metrics related to fraud detection, model precision/recall, and user experience. • Conduct deep dives into fraud patterns and emerging attack vectors. • Support product launches and enhancements with clear positioning and documentation. • Enable internal teams and customers to understand and effectively use decisioning capabilities.
• 3–5 years in product management, preferably in identity verification, fraud prevention, or other ML-driven products. • Strong understanding of APIs, SQL queries, databases, and product architecture. • Experience working closely with ML models, including understanding model outputs, evaluation metrics, and tradeoffs. • Exposure to image processing, OCR, or document verification systems is a strong plus. • Familiarity with fraud detection techniques, identity verification flows, or risk-based decisioning systems. • Comfortable working with data, writing queries, and deriving insights to inform product decisions. • Ability to balance technical complexity, customer needs, and business impact in decision-making. • Experience working directly with customers, especially in complex or high-stakes environments. • Strong ability to explain complex technical concepts clearly to both technical and non-technical audiences. • Proven ability to work cross-functionally with Engineering, Data Science, and go-to-market teams.
• Offers Equity • Offers Bonus
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