Own the Trust & Safety product strategy and roadmap translating business risk and user insight into a clear, prioritised plan.

Shift the function from reactive incident response to proactive, intelligence-driven fraud prevention: build the Risk Engine, data signals intelligence, anomaly detection, and investigation tooling that make this possible.

Ship AI-native T&S product experiences: partner with Data Science and Engineering to design, prototype, and productionise real-time detection and decisioning systems using ML models, LLMs, and behavioural signals.

Balance fraud mitigation with growth protection—ensuring T&S interventions do not unnecessarily create friction for legitimate users or throttle marketplace supply/demand. Make hard, evidence-based trade-off decisions.

Define and track the right T&S success metrics: fraud loss rates, false positive/negative rates, time-to-resolution, user trust scores, and financial exposure. Communicate impact in business terms to senior leadership.

Partner closely with Engineering leads, Data Science, Legal, Compliance, and Operations—holding shared accountability for outcomes and navigating competing priorities.

Build long-term instrumentation, monitoring, and evaluation capabilities to measure fraud rates, detection model performance, and contributor/user impact at scale.

Establish business cases quantifying fraud losses and ROI of prevention investments; secure resources and drive prioritisation grounded in data.

Ensure products and strategies meet local and regional compliance, legal, and security requirements across all markets.

Apply AI to how you operate as a PM: faster threat analysis, synthetic user research on abuse patterns, AI-assisted spec writing, automated experimentation pipelines—whatever moves the needle on velocity.

Represent Trust & Safety at the leadership level, presenting strategy, risk posture, and results clearly to executive audiences.

Significant product management experience in the digital sector: consumer facing platform, marketplace, mobility, e-commerce, classifieds, fintech, or similar high scale environment.

Proven experience owning trust related products or problem spaces such as Trust & Safety, Fraud Prevention, Risk, Identity & Verification, Marketplace Integrity, Account Security, Abuse Prevention, Payments Risk, or Compliance Technology.

Track record of building scalable systems that proactively detect, prevent, and mitigate abuse, fraud, risk, or other trust related issues, rather than relying solely on manual or operational processes.

Strong analytical and data driven mindset, with experience defining success metrics, evaluating impact, and making prioritization decisions based on evidence and measurable outcomes.

Experience partnering closely with Engineering, Data Science, Operations, Legal, Compliance, and other cross-functional stakeholders to deliver complex products in regulated or high-risk environments. Experience in vendor management and collaboration.

Experience building, deploying, or working closely with machine learning, AI, risk scoring, decisioning, detection, recommendation, or automation systems. Hands-on experience with AI-powered trust or fraud products is a plus.

Demonstrated ability to balance user experience, marketplace growth, operational efficiency, and risk mitigation, making thoughtful trade offs that protect both users and the business.

Comfortable operating in ambiguity, taking ownership of complex problem spaces, influencing senior stakeholders, and driving strategy and execution across multiple teams.

Strong core product muscle that transfers across fraud domains—you've stepped into unfamiliar threat vectors, oriented fast, and delivered. Domain specificity matters; rigid domain lock-in does not.

Well versed in building, iterating core Data (Science) products at scale

Experience building trust, risk, fraud, or safety products across multiple international markets and regulatory environments.

Familiarity with emerging regulations and industry trends affecting online platforms, digital marketplaces, payments, AI, and consumer trust.