Posted over 1 year agoOur mission In 2017, immigrants worldwide sent over $600 billion home to family and friends, dwarfing foreign governmental aid. In the age of cheap, quick transfers through services like Paypal and Venmo, these people are trekking to stores to pay fees averaging over 7% for transfers that typically take 24 hours or more. Wave's mission is to change that by making sending money anywhere in the world easy and affordable. Since 2014, our app has allowed Africans in the US, the UK, and Canada to send money instantly to mobile money wallets in Kenya, Uganda, Ghana, & Tanzania, saving our users over 70% relative to Western Union and MoneyGram. We’ve been able to keep our rates low because we’ve been able to control fraud on these corridors. We recently piloted remittances to Nigeria, where we're growing quickly and are looking to rapidly expand throughout Africa next year. That's where you come in:How you'll help us achieve it We've built a world-class team who bring their experience working for organizations as diverse as Google, Western Union, the United Nations and Doctors Without Borders to their work at Wave. As the first Corridor Fraud Owner, you'll not only own the fraud strategy for your corridors, driving key fraud KPIs through a continual loop of analysis and process improvement, but also help Wave define this position within a fast-growing fraud team. Your insights directly result in heuristic defenses and heavily influence model development decisions and the Risk engineering backlog. This role will be a 50/30/20 split between analysis, process optimization, and technical feature requirements capture. On any give day, you will:Actively monitor fraud corridors, identifying new patterns and trends as they emerge. You will identify fraud MOs and individual fraudsters by analyzing customer behavior and chargeback data. Develop heuristics to defend against emerging patterns and work with engineering and data science teams when developing new insights.Establish our fraud segmentation policies for your corridors.Work with Risk Ops to ensure that they can effectively review fraud cases produced by your corridor. Evaluate vendor services and tooling, actively monitoring the vendor landscape for more effective tooling and lowering our decision costs. Maintain our Risk Ops playbooks — our standard operating manual for interpreting our risk flags/indicators that our operations teams use to disposition fraud cases. Work to make fraud protection as frictionless for our users as possible.Key detailsLocation: Our company is 100% remote. You can be based anywhere in the United States, Canada, United Kingdom, Italy, Belgium or GermanyCompensation: $80,000 - $120,000 (or local equivalent) per year depending on experience, plus equity. Length of position: Permanent. RequirementsFluency in English.Local work authorization (wherever it is you'd like to be based).Have a quantitative or analytical background and have previously in an analytics environment (investment banking, management consulting, product owners of analytics teams). Folks with engineering, CS, economics or finance would be a good fit. Have a solid grounding in SQL. Comfort communicating (written and verbal) with leadership, engineering and operations teams. You might be a good fit if youAre happiest analyzing financial and behavioral data to spot rare-occurrence trends in large data sets and excited at the prospect of owning fraud KPIs for an entire corridor. Can work with and communicate effectively with a multi-disciplinary team. Are comfortable setting up A/B or other experiments to understand the impact of new fraud defenses on our customers. Are excited at the prospect of working with front-line operations teams, helping them meet their our KPIs by optimizing their training, workflow and tools. Recognize that data can have a bias and hold yourself to the highest standards in ensuring that our fraud defenses are effective without being discriminatory.Bonus points if youAre familiar with the diaspora communities we serve.Have background in Fraud (particularly CNP fraud).Have background or are willing to learn Python for data analysis and/or have used Jupyter notebooks for reproducible analysis. R and R Studio also get bonus points.