Full-time | San Francisco | California | United States
There’s no denying it: all online marketplaces can provide opportunities for fraudsters and malicious actors. Our ability to track, record, and combat fraud at scale is a huge part of our competitive advantage. Eventbrite is growing at a massive rate, and our team is keeping up with the volume. Last year we processed $2B in transactions and over 35M paid tickets, that’s a huge exposure, and we’re charged with keeping it secure.
We are looking for an experienced Risk Analyst to join our cross-functional spam & fraud fighting efforts. Analysts on Eventbrite's Risk Team specialize in identifying fraud patterns, working on advanced automated prevention mechanisms, creating and tracking fraud & spam metric; as well as creating, insightful, accurate and data driven policies and review methodologies with an emphasis on automation. Our goal is to make things easy for our growing community of users while protecting our system from abuse and fraud.
The Risk Analytics team is a small group with diverse backgrounds. We are analysts, data scientists and engineers, with different quantitative and qualitative analytical skills. Our varied experiences help us look at the same problems sets in different ways to extract real insight. Hear more about our work directly from the team.
Design and write automated rules to prevent fraud, spam and other abuse on the platform
Test and track rule performance
Identify incidents and patterns of abuse using various techniques and data analysis tools
Create and implement fraud and spam policies
Research spam, fraud and user behavior to contribute to machine learning models, rules and other detection systems
Collaborate with analysts, operations specialists, data scientists and engineering to create tools, rules and prevention mechanisms
Solve complex problems by gathering and distilling web, financial, and behavioral data into actionable findings
Maintain and improve fraud and spam metrics, as well as track, analyze and communicate these metrics
Maintain strong domain knowledge of the worlds of spam and fraud including prevention techniques and technologies
THE SKILL SET
3+ years of analytics experience or a related technical discipline
Master of SQL and Excel (MySQL/Hive preferred)
Proficiency in Python preferred, or experience in another scripting lauguage (R, Matlab, etc.)
Familiarity with Internet technologies and protocols
The ability to think quickly and learn even faster
Ability to work well in a highly collaborative environment
A proven ability to formalize complex ideas and process into a well defined logic
Strong interpersonal, verbal, and written communication skills
BA or BS Degree or higher
Experience in fraud or spam
Knowledge of BI tools like Tableau
Experience with log-analysis tools like Splunk
Active Eventbrite user with a passion for live events
Eventbrite powers ticketing and registration for more than two million live experiences each year, hosting the world’s largest online selection of events. We build technology that allows anyone to create, share, find and attend events of all kinds. Music festivals, marathons, conferences, hackathons, political rallies, fundraisers, gaming competitions— you name it, we power it. Meet some of the team.
Interested in joining our team, but waiting for the right time or the right role? Let's keep in touch! We’re a quickly growing team that's always looking for awesome talent like you.
We host regular meetups, happy hours, game nights, and more that are open to our community. Tell us a bit about yourself and we'll get you on the list for our next shindig, keep you up to date with what we're up to, and make sure you're the first to know about new opportunities.
Thank you! We'll be in touch.
Welcome to the Briteside
Get ready for spontaneous applause, impromptu brainstorms, and the contagious excitement we bring to the office each day. We’ve built a team that does great work and has an awesome time doing it—and we’re always looking for more whip-smart people to pipe up, dive in, and get their hands dirty with us.