Applied Science Manager, Seller Partner Trust and Store Integrity Science - Global Risk Intelligence and Prevention

Description

We are looking for an Applied Science Manager III to lead a team of applied scientists building next-generation AI-powered seller risk detection systems. This role sits at the intersection of deep technical science, strategic planning, and cross-organizational partnership. GRIP Science serves a complex stakeholder landscape: enforcement teams, policy owners, marketplace operations, peer science orgs, and senior leadership, each with distinct timelines and priorities.

The right leader for this role will navigate that landscape with clarity, balancing urgent operational needs against the long-term scientific investments required to stay ahead of adversarial actors at scale.

You will independently own the vision, roadmap, and execution for a critical detection surface, defining what to build, what to defer, and how to measure success. You will set and maintain a high bar for scientific rigor while cultivating a team culture that rewards creative problem-solving and principled risk-taking.

Key job responsibilities

Strategy & Stakeholder Partnership

- Define the scientific vision and multi-year roadmap for your team's detection domain, ensuring alignment across a broad set of stakeholders with competing priorities and timelines

- Develop strong working relationships with enforcement, policy, operations, and engineering partners; serve as the trusted scientific voice in cross-functional discussions

- Exercise judgment in sequencing work. Distinguish between high-urgency requests that warrant immediate response and those better addressed through systematic, durable solutions

- Influence org-level planning (OP1/OP2) through compelling written narratives and data-driven proposals that articulate both near-term deliverables and long-term scientific bets

- Proactively communicate trade-offs to leadership and stakeholders, building trust through transparency about what your team will and will not prioritize in a given cycle

Science & Technical Leadership

- Lead a team building state-of-the-art detection models that leverage modern AI techniques, including deep learning, foundation models, and generative AI, to identify novel abuse patterns at scale

- Set and uphold a high standard for scientific methodology: model validation, experimentation rigor, reproducibility, and interpretability of results

- Evaluate end-to-end scientific proposals for soundness, scalability, and production readiness; know when to push for deeper investigation and when to ship

- Foster a culture of scientific curiosity and invention. Encourage the team to challenge assumptions, explore out of the box approaches, and invest in research that creates step-function improvements rather than incremental gains

- Identify where emerging AI capabilities (e.g., large language models, multimodal reasoning, self-supervised learning) can be applied to unlock new detection signals or fundamentally reshape existing pipelines

- Make informed trade-offs between model sophistication, delivery timelines, and operational sustainability

Execution & Operational Excellence

- Scope scientific projects, set priorities, and drive schedules; readjust decisively when incoming signals warrant a change in direction

- Structure work to reduce exposure to classic failure modes: ambiguous requirements, untested assumptions, under-instrumented models

- Establish mechanisms and metrics to continuously measure model effectiveness, enforcement precision, and downstream business outcomes

- Drive production readiness: monitoring, alerting, on-call practices, and rapid response for AI/ML systems processing millions of daily decisions

Team Building & Development

- Build and lead a high-performing team of applied scientists; attract and develop talent that combines…