About us:

At Transak we are making Web3 applications accessible. We do this with enterprise-grade developer tools to allow web3 applications such as Metamask, Decentraland, and Anchor protocol to onboard users from fiat to crypto, delivered directly to their wallet. Without Transak, users of these applications would have to leave the in-app onboarding flow and figure out how to buy crypto on a 3rd party exchange and send it to their wallet.

We are looking for a Senior Fraud Analyst based in the UK/EU or US who will form part of our Compliance Team to build our fraud detection and prevention framework and controls.

Responsibilities:

  • Develop and implement fraud/risk rules and strategies to improve fraud detection accuracy with maximum automation
  • Analyse large data sets and perform ad-hoc analysis to identify fraud trends, take action to stop fraud activity, enhance fraud rules, and improve automation
  • Manage and develop fraud policies and processes to identify and minimise fraud
  • Monitor and validate the fraud rule performance to ensure optimal results
  • Work with modellers to evaluate and improve model performance by identifying data gaps or new variables
  • Identify and build fraud metrics for KPIs, reports and dashboards to monitor and benchmark performance
  • Collaborate closely with and provide Product Managers with business requirements that would improve risk tools and detection of emerging e-commerce fraud trends
  • Perform business unit and user acceptance testing and coordinate process changes for new code releases
  • Develop and continuously improve process to identify, communicate, and escalate fraud activity to internal and external stakeholders

Requirements:

  • 5+ years fraud risk management experience in e-commerce/m-commerce with traditional and alternative payment methods. Ability to analyse fraud patterns, create empirical rules and prevention strategies to identify and mitigate fraud attacks.
  • Extensive knowledge in card-not-present fraud schemes, its risk prevention methods and detection tools for digital, virtual and physical goods.
  • Experience mitigating online fraud, such as account takeover, phishing, online card testing, etc.
  • Strong quantitative analytical experience, including background with statistical modelling & analysis.
  • Experience in regression modelling, neural networks, decision trees, and similar methodology for detecting and preventing online fraud
  • Ability to analyse large transactional data sets, interpret ambiguous situations, and make decisions under pressure
  • Strong understanding of the online payments landscape across all participants – issuer, merchant, acquirer and network.
  • Excellent written, oral and presentation skills and an ability to synthesize information and make clear, concise recommendations on a course of action
  • Creative, team-focused, and effective problem solver
  • Willingness to do what it takes to get the job done