Poshmark
Staff Risk Strategy Analyst
US California (Redwood City) - Office · Staff+
Sponsorship not specifiedDetected 4 days ago
PythonSQLMachine LearningData ScienceStatisticsA/B TestingStakeholder ManagementResearchCommunicationProblem Solving
About the role
- 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.
- This role will be responsible for designing and optimizing sophisticated risk decisioning strategies that mitigate fraud and abuse while minimizing friction for legitimate users.
Responsibilities
- 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
- 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
- Collaborate cross-functionally with Product, Engineering, Trust & Safety Operations, Payments, Customer Experience, and Analytics teams to influence roadmap priorities and improve marketplace trust
- Develop subject matter expertise across evolving marketplace abuse vectors, fraud trends, and industry best practices
- Mentor analysts and cross-functional partners while helping elevate the overall analytical rigor and strategic maturity of the organization
Requirements
- 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
- Strong analytical and problem-solving skills with the ability to break down complex problems and solve from first principles
- 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
- 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 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
- Ability to navigate ambiguity, prioritize effectively, and drive complex cross-functional initiatives in a fast-paced environment
- Passion for protecting marketplace integrity and building trusted user experiences at scale
Nice to have
- Strong proficiency in SQL and experience working with large-scale transactional and behavioral datasets
- experience with Python or R preferred
Benefits
- 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
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This listing is sourced directly from Poshmark's careers page and normalized into a canonical job model.