SHIELD is a device-first risk AI platform that helps digital businesses worldwide eliminate fake accounts and stop all fraudulent activities. SHIELD identifies the root of fraud with the global standard for device identification (SHIELD Device ID) and actionable risk intelligence, empowering businesses to stay ahead of new and unknown fraud threats. We are trusted by global unicorns like inDrive, Alibaba, Swiggy, Meesho, TrueMoney and more. With offices in San Francisco, Miami, London, Berlin, Jakarta, Bengaluru, Beijing, and Singapore, we are rapidly achieving our mission – eliminating unfairness to enable trust for the world.
Responsibilities
As a Risk Analyst, you will be involved in supporting the risk operations by conducting data analysis of large datasets to discover fraud trends and patterns, thereafter being involved in designing long-term solutions to fight fraud. The insights you provide will contribute towards optimizing risk management strategies and creating business value by enabling trust for our clients. Responsibilities include:
- Handle end to end process from data analysis, deriving insights, summarizing, and presenting recommended actions to stakeholders in order for us to stay ahead of new and unknown fraud.
- Monitor any new or existing implementations and/or deployments relating to risk, keeping up to date with the latest metrics of our clients and their respective potential fraud trends and analyses.
- Timely response to alerts for any risk related escalations.
- Deep dive investigation on potential issues such as changes to clients’ metrics (e.g., sudden dip or spike), communicate and work with relevant stakeholders to ensure timely resolution.
- Optimize fraud detection by rapidly identifying emerging fraud trends through data-driven analysis in complex and large dataset such as device metadata, user data, payment data – and coming up with proposals to address them and preventing future occurrence.
Requirements
- 1 – 3 years of experience as a hands-on analyst with risk knowledge.
- Minimum Bachelor’s Degree in Computer Science, Data Sciences, Statistics, Mathematics, or other related fields.
- Working experience in handling large-scale unstructured data.
- Experience in using business intelligence tools such as Microsoft Excel, Tableau, and Qlik Sense.
- Experience in SQL or other data handling tools a bonus.
- Ability to take initiative in a fast-moving and dynamic environments, and take timely actions to prevent risk of fraud.
