Staff Risk Strategy Analyst

Poshmark is the leading fashion marketplace where style comes alive through discovery, self-expression, and human connection. Powered by a vibrant community of 165 million members, Poshmark brings real people and taste to shopping through a social experience shaped by shared discovery. Buying and selling fashion feels simple, joyful, and personal, while every item tells its own story. Poshmark empowers sellers to grow meaningful businesses, keeps fashion in circulation longer, and gives shoppers access to unique and trusted finds, from everyday pieces to one-of-a-kind vintage and luxury.

Poshmark is redefining the future of social commerce by creating a trusted, engaging marketplace where millions of buyers and sellers connect every day. As our marketplace continues to scale, maintaining trust across the ecosystem is critical to enabling sustainable growth, protecting our community, and delivering exceptional customer experiences.

We are looking for a Staff Risk Strategy Analyst to develop and scale marketplace risk strategies across buyer, seller, and account-level abuse vectors. This role will be responsible for designing and optimizing sophisticated risk decisioning strategies that mitigate fraud and abuse while minimizing friction for legitimate users.

This role operates at the intersection of analytics, fraud strategy, trust & safety, identity, payments risk, and platform integrity. The ideal candidate combines deep analytical expertise with strong business judgment and a passion for solving complex marketplace abuse problems. They will partner closely with Data Science, Product, Engineering, Operations, and Trust & Safety teams to identify emerging threats, drive strategy innovation, and improve risk decisioning across the Poshmark ecosystem.

This role will leverage internal and external risk platforms, data tools, and orchestration capabilities to rapidly design, test, deploy, and optimize risk strategies across the customer lifecycle.

• Develop and deliver marketplace risk strategies and policies across buyer fraud, seller abuse, account integrity, payment fraud, refund and return abuse, spam, and trust & safety domains

• Use advanced analytics and large-scale marketplace data to identify abuse patterns, quantify risk exposure, and develop actionable mitigation strategies

• Design, implement, and optimize risk decisioning strategies across internal and external risk tooling to balance fraud prevention, user experience, and marketplace growth

• Partner closely with Data Science teams to evaluate, operationalize, and monitor machine learning models related to account risk, listing integrity, comment abuse, identity risk, and behavioral anomaly detection

• Drive experimentation frameworks and hypothesis-driven testing methodologies to evaluate policy effectiveness, model performance, operational impact, and customer friction

• Define, monitor, and improve key risk and business performance metrics to measure strategy effectiveness and support data-driven decision making

• Conduct portfolio analyses to identify emerging fraud trends, systemic vulnerabilities, and opportunities for automation and optimization

• Translate complex analytical findings into clear, actionable business recommendations in a simple, compelling, and data-driven manner

• Collaborate cross-functionally with Product, Engineering, Trust & Safety Operations, Payments, Customer Experience, and Analytics teams to influence roadmap priorities and improve marketplace trust

• Apply strong business acumen and first-principles thinking to solve ambiguous and highly complex marketplace risk challenges

• Develop subject matter expertise across evolving marketplace abuse vectors, fraud trends, and industry best practices

• Establish monitoring frameworks, KPIs, and governance processes to ensure ongoing strategy performance and rapid response to emerging threats

• Mentor analysts and cross-functional partners while helping elevate the overall analytical rigor and strategic maturity of the organization

• Bachelor’s degree in a quantitative field such as Statistics, Mathematics, Economics, Computer Science, Finance, Operations Research, or related discipline with 8+ years of relevant experience, or advanced degree with 6+ years of experience in fraud, risk, trust & safety, or advanced analytics

• Deep experience developing and optimizing fraud, abuse, or trust-related strategies within marketplace, e-commerce, fintech, payments, or platform ecosystems

• Strong proficiency in SQL and experience working with large-scale transactional and behavioral datasets; experience with Python or R preferred

• Experience leveraging internal and third-party risk decisioning, orchestration, identity, or fraud prevention platforms

• Strong understanding of marketplace fraud vectors including account abuse, payment fraud, refund abuse, fake accounts, spam, listing abuse, social engineering, and platform manipulation

• Experience partnering with Data Science and Machine Learning teams to operationalize predictive models into production risk workflows

• Demonstrated success designing experiments, measuring impact, and balancing fraud mitigation with customer experience and business growth objectives

• Strong analytical and problem-solving skills with the ability to break down complex problems and solve from first principles

• Ability to navigate ambiguity, prioritize effectively, and drive complex cross-functional initiatives in a fast-paced environment

• Excellent communication, storytelling, and stakeholder management skills with the ability to influence both technical and non-technical audiences

• Strong business acumen with the ability to translate data insights into strategic recommendations and measurable business impact

• Passion for protecting marketplace integrity and building trusted user experiences at scale