Product Manager - Device & Behavior

Shape the future of trust in the age of AI At Oscilar, we're building the most advanced AI Risk Decisioning™ Platform. Banks, fintechs, and digitally native organizations rely on us to manage their fraud, credit, and compliance risk with the power of AI. If you're passionate about solving complex problems and making the internet safer for everyone, this is your place https://oscilar.com/careers.   WHY JOIN US: - Mission-driven teams: Work alongside industry veterans from Meta, Uber, Citi, and Confluent, all united by a shared goal to make the digital world safer. - Ownership and impact: We believe in extreme ownership. You'll be empowered to take responsibility, move fast, and make decisions that drive our mission forward. - Innovate at the cutting edge: Your work will shape how modern finance detects fraud and manages risk. THE PROBLEM: A user hitting a fintech, marketplace, bank, or crypto platform in 2026 could be a human, an autonomous agent acting on a human's behalf, a bot impersonating either, or a coordinated attacker. Device intelligence and behavioral biometrics were built to answer "is this a real human on a real device." That question is no longer sufficient. Oscilar is building the next generation of it. Every risk decision — auth, fraud, onboarding, mule detection, AML — now depends on distinguishing bot, human, agentic, and attacker in the first 300ms of a session, and explaining that decision to an analyst, an auditor, and a regulator. The engineering and R&D team tackling this at Oscilar is the deepest in the industry. We're now hiring the first product lead to shape the strategy, own the GTM, and drive adoption for the next generation of digital identity at Oscilar. WHAT YOU'LL OWN: - The D&B product strategy, operations, execution, and customer success - The model layer that turns raw signals into features our fraud and onboarding agents consume as tools - The analyst experience and operations that turn those signals into decisions inside customer workflows - The D&B data network and the model program - GTM for the pillar — you'll sit in customer deals with the AE, train SEs, and close the loop from strategy to adoption to execution WHAT YOU'LL BUILD: - D&B SDK (iOS, Android, web) — passive, cold-start friendly, privacy-scoped under ATT and Play Integrity. - Signal pipeline — high performance, resilient to poor networks, fully observable - Passive telemetry model layer — behavioral biometrics, anomaly scores, coached-fraud and APP-scam detection, headless-browser and agent-traffic detection - Agentic-identity signal surface — distinguishing authorized agents from adversarial bots, with consent, delegation, and provenance signals - D&B data network — cross-customer signal strategy, consortium data, consent and hashing design - Foundation-model program — self-supervised models on session sequences, consumed by our risk agents as tools - Analyst signal experience — how fraud strategists read, drill into, and override TrustScores - Attacker ecosystem mapping — killchain patterns and red-teaming REQUIREMENTS: - 5+ years PM experience, 8+ preferred - Personally shipped a device intelligence, behavioral biometrics, or session-signal product to production at scale — vendor-side or in-house - Taken a product 0→GA and owned GTM end to end: pitch narrative, sitting in AE deals, alpha with fewer than 10 customers, integration time cut meaningfully - Buyer credibility with VP Fraud, Head of T&S, Head of Auth or Identity, or CRO — can reframe the "commodity" objection in five minutes - A real point of view on agentic digital identity, publicly demonstrated (blog, talk, essay, or shipped feature) - AI-native — a view on moving from handcrafted features to a foundation-model program, and on how risk agents consume features as tools - SDK and technical fluency: mobile parity, cold-start telemetry, entropy vs. payload, ATT and Play Integrity, fingerprint stability under browser hardening - Understands FPR and precision-recall tradeoffs and why the operating point matters more than AUC - Data-network instincts — consent, hashing, network-effect design

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