.Who we are?Clip is revolutionizing the payments landscape in Mexico! We are empowering people to exchange value directly from a mobile device. Clip enables anyone to accept card payments, at any time, and anywhere by turning your smartphone or tablet into a card terminal. We're a well-funded, fast-growing FinTech startup. We are the leaders in our market and are accelerating to extend our lead and move into new markets. The Role:We are looking for a Fraud Prevention Analytics Manager to be part of this amazing and fast-growing fintech. This candidate will be responsible for defining the risk analytics strategy and working with different areas in Clip to achieve the goals. S/he will manage and implement the strategic process for the area, should prevent and timely detect fraud, scaling of critical cases and incidents, ensure the maintenance of an acceptable level of fraud risk to contribute to the achievement of the objectives of the organisation, and generate a positive customer experience in the use of Clip. S/he will provide feedback in a professional manner, should be able to step-back and communicate both the strategic and immediate implications on priorities and must have strong written and verbal communications skills. What will I do? Responsible for defining the fraud prevention analytics strategy, both for payments (face-to-face and e-commerce) and Financial Services business. Implementation, monitoring and validation of models in order to maximise approval, minimise chargebacks losses, providing excellence in the merchant experience. Design and maintain risk rules to understand new fraud patterns. Manage and control of Fraud Management. Control and monitoring of the main KPIs of the area that impact the business. Scaling of risks, vulnerabilities, deviations and relevant cases. Analyse and redesign the Fraud process continually. BI and Ad Hoc reporting. Ideal Candidate: BA in Actuary, Economics, Statistics, Mathematics, Engineering or similar technical studies. Master in Data Mining, Data Science, MBA is a plus. Minimum of 5 years of experience working in payments risk with a strong knowledge of risk & fraud prevention (both Card Present and Card Not Present). Strong knowledge of fraud, chargeback, and scheme rules and are able to provide detailed requirements to internal and external customers. Experience in developing ML models, implementing and executing models in order to optimise risk management. Ability to effectively communicate the importance of risk management in payments optimization. High level of self-motivation and always looking for ways to improve and make our processes more efficient. Strong data analysis and correlation skills with ability to work through complex and unfamiliar data sets. Bonus points if you have experience creating impactful dashboards using BI tools (such as Looker or Sisense). Knowledge in technologies and fraud prevention