Eventbrite needs to design, implement, and track risk prevention policies to ensure creators get paid and attendees find events, while mitigating fraud and maintaining a positive user experience.
Requirements
- Expertise with SQL including experience working in complex data environments (>2 years)
- experience developing monitoring and dashboards, including design and maintenance of data transformations using tools such as DBT
- Command of a set of practical statistical analysis packages including pandas, Microsoft Excel, and/or similar tools to perform predictive analysis
- Experience with data processing and scripting in Python including comfort with version control tools (e.g. git) and test-driven development (>2 years)
- Direct experience in an anti-abuse space such as fraud, spam, content policy, or trust and safety
- Experience working closely with machine learning and AI-driven teams and associated knowledge of statistics
Responsibilities
- design, implement, and track the risk prevention policies at the center of our risk detection and mitigation strategy
- drive analytical efforts to source data from Eventbrite’s wide variety of product features
- leverage data to design effective, low friction policies
- collaborate with colleagues in engineering to use our in-house decisioning platform to quickly design, test, and ship data-driven rules
- implement improvements to that platform to move faster
- work with data scientists to leverage and collaborate on improving machine learning and AI models
- partner with other analytical teams to track the impact on the business as a whole
Other
- Proven ability to research and design data-driven policies, and to communicate findings to non-technical audiences including cross-functional decision makers
- Collaborative mindset and interest in gaining domain expertise in payments, content moderation, and risk prevention spaces
- Active Eventbrite user with a passion for live events
