We are looking for experienced engineers to help detect and reduce risk to Robinhood. The ideal candidate is passionate about understanding the different risk vectors at a fast growing company and building engineering solutions to mitigate these risks. This team is part of the Data Team at Robinhood.
In this role you will:
- Work with stakeholders across teams such as Finance, Market Operations, Fraud Operations and Compliance to understand the biggest risks to Robinhood
- Build real-time risk monitoring systems to mitigate the biggest risks to Robinhood.
- Work closely with Data Scientists to build statistical stress testing platforms to quantify risk exposure under various scenarios including black swan events.
- Work on our real-time fraud engine to keep bad actors out of Robinhood by using machine learning to quantify the riskiness of user actions on the Robinhood platform.
- Work closely with the fraud operations team to build tools to detect and investigate fraud rings.
Some things we consider critical for this role:
- 4+ years of software engineering experience
- Familiarity with Kafka, Spark or other similar technologies
- Strong communication skills with both technical and non-technical audiences
- Passion for learning about the Financial Systems and owning projects end to end
Some things that would be amazing to have for this role:
- Experience in building Risk monitoring systems in the Financial Services industry
- Deep knowledge of the financial industry and the various instruments such as equities, options etc
- Experience of building fraud detection and prevention systems
Technologies we use:
- Faust ~ Built and open sourced by our team
- ELK (Elasticsearch, Logstash, Kibana)