Software Engineer - Payments Risk | Twitter, Inc. | San Francisco, CA
Software Engineer - Payments Risk
Software Engineering | San Francisco, CA
About this Job:
Twitter is building a next generation advertising platform, a key piece of which is self-serve advertising through credit card payments. As a payments risk engineer, you will build systems required to identify and prevent payments fraud on Twitter’s advertising platform. You’ll be building the first generation of fraud-detection systems and operational workflow, moving seamlessly between production coding and data analysis. As Twitter advertising grows, your contributions will be critical to ensuring its continued success for Twitter, our advertisers, and our users.
Responsibilities:
Twitter is building a next generation advertising platform, a key piece of which is self-serve advertising through credit card payments. As a payments risk engineer, you will build systems required to identify and prevent payments fraud on Twitter’s advertising platform. You’ll be building the first generation of fraud-detection systems and operational workflow, moving seamlessly between production coding and data analysis. As Twitter advertising grows, your contributions will be critical to ensuring its continued success for Twitter, our advertisers, and our users.
Responsibilities:
- Design, build and maintain a world-class payment fraud detection and prevention system
- Build, test, deploy, and refine predictive fraud models using the various large data sources available
- Build an intelligent credit risk framework, enabling revenue by identifying good vs. bad users and adjusting limits accordingly
- Work with risk analysts to define and track key operational metrics (chargeback rates, false +/- rates etc.)
- Work closely with cross functional teams in product, operations, and finance
- Strong quantitative/statistics background to support data-driven decision making
- Experience using SQL and database systems, e.g., Mysql, Vertica.
- Experience with software engineering best practices (e.g. unit testing, code reviews, design documentation)
- Be extremely nimble, able to identify emerging and exigent fraud trends, design and implement novel solutions under pressure
- BS, MS, or PhD in Computer Science, Statistics or a related technical field or equivalent work experience
- Experience with online payments, e-commerce, and fraud prevention
- Experience with stats tools like R, Weka, SAS, Tableau, or Matlab
- Avid Twitter user
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