Fraud Engineer
The Opportunity
Vivid Seats is the largest independent online ticket marketplace, sending 40,000 fans to live events every day. Experiences Matter. The importance of them is expanding rapidly as the industry continues to grow year over year. Working at Vivid Seats puts you front and center at the opportunity to scale our best in class platform that allow our fans to sit closer and see more.
At Vivid Seats, you will have the opportunity to work with flexibility and the speed of a startup while operating at massive, profitable scale. We keep our teams lean, giving every single employee direct accountability to creating a positive ticket buying experience. We are relentless and move quickly to release new features and content to the site and mobile app daily. Your ideas are heard and implemented, your hard work rewarded. Being a part of our team means that have the ability to drive impact and own the innovation that allows us to connect our tens and millions of unique monthly users to the memorable experiences that live events create.
Our Fraud Engineer works between the Fraud and Risk team, Engineering, and senior management to identify and prevent fraudulent threats.
The Fraud Engineer will also have ownership of building and deploying machine learning models and identifying new approaches and methodologies, improving the overall performance of the business.
This role will help drive authentication policy/strategy analysis and projects to ensure a balanced approach to customer experience and fraud prevention.
As a Fraud Engineer, you will refine and deploy detection algorithms to identify a variety of fraud use cases including transaction fraud, spam, account takeover, fake account applications, and content abuse for enterprise customers. You will work with product and engineering teams to develop internal tools and UI dashboards that track and measure various fraud detection metrics.
Responsibilities
- Build machine learning models for fraud detection and document data extraction
- Drive the definition of the machine learning infrastructure and pipeline to build and scale machine learning
- Define metrics for feature evaluation and model performance
- Partner with various business and technical partners to analyze and implement authentication processes and tools that effectively manage authentication risk and customer experience
- Evaluate and recommend control enhancements which will improve business controls and/or reduce impacts to good customers
- Transform business requirements into creative business solutions using existing products and new ideas that demonstrate out-of-the-box thinking
- Prepare project status reports and presentations to keep leadership and other stakeholders informed of project status, ongoing issues and recommended solutions
- Stay up to date on fraud prevention techniques and emerging trends
To be successful, you'll need
- 5+ years of relevant experience - 3+ two years of experience reviewing and investigating alerts, flagging unusual and suspicious activity, including fraud patterns strong preferred
- Extensive knowledge of machine learning algorithms, techniques, available implementations in python and frameworks
- Strong point of view on how to build scalable machine learning infrastructure
- Ability to write high performing, high quality code in python
- Excellent engineering and problem-solving skills
- Familiarity with transaction monitoring systems and procedures
- Knowledge & Experience in QOS & SIP End to End call flow troubleshooting of VoIP services which may require coordination with other teams
- Creativity, fearlessness and an unwavering commitment to putting the customer first, elevating your team and ownership over outcomes