Eventbrite is a big, bustling marketplace where anyone can post an event in minutes or buy a ticket in seconds. The Risk & Fraud Engineering team works behind the scenes to ensure our creators get paid and our attendees find amazing events. We make great experiences happen reliably and without unnecessary risks even as Eventbrite launches innovative features and expands into new markets across the world. Our Engineers and Decision scientists make sure we keep up without our organizers noticing by designing low profile, high precision, data-driven solutions to the ever-changing landscape of threats.


The Risk & Fraud Engineering team is a high-performing, multi-disciplinary team that works closely with Fraud Analysts and Data Scientists. We work together toward the common goal of making Eventbrite the trusted marketplace for live experiences. We are vigilant for emerging problems, and we strive to solve them together with a flexible approach and a thirst for innovative solutions to complex problems. 


You will design, implement, and track the risk prevention policies at the center of our risk detection and mitigation strategy. You will work with in-house platform operations and policy experts to understand the details of what’s working well and where we have opportunities to fill gaps. You will drive analytical efforts to source data from Eventbrite’s wide variety of product features, and then leverage it to design effective, low friction policies. You will collaborate with our risk engineering team to leverage our in-house decisioning platform to quickly design, test, and ship data-driven rules. You’ll work with our data scientists to layer in understanding from machine learning models or even improve them. You will partner with analysts to design performance tracking, enabling iterative design, and nimble prioritization. 


  • Proven ability to research and design data-driven policies in a detailed-oriented domain
  • Ability to facilitate and drive cross-functional collaboration, gaining domain knowledge from in-house experts, and accurately explaining anticipated results
  • Expertise with SQL, including experience working in dynamic data environments (>2 years) with experience developing, monitoring of dashboards
  • Command of a set of practical statistical analysis packages such as pandas, Microsoft Excel, or similar 
  • Experience with data processing in Python (>2 years)


  • Experience in an anti-abuse space such as fraud, spam, content policy, or trust and safety.
  • Familiarity with ML Ops concepts and tools for model deployment, monitoring, and lifecycle management.
  • AWS certification(s) such as AWS Certified Solutions Architect - Associate or AWS Certified Data Analytics - Specialty is a plus.
  • Understanding of big data processing technologies like Spark, Hive, or Presto
  • Active Eventbrite user with a passion for live events