Data Scientist (Risk Management)

Our business is fundamentally data-driven, harnessing a cloud-native platform to support tens of millions of cryptocurrency users. Engineers and data scientists across the company utilise this platform to carry out meaningful and impactful analysis that fuels ongoing innovation. As a data scientist, you will have the opportunity to work with vast datasets (at petabyte scale) and cutting-edge machine learning infrastructure to develop data products that serve our extensive global user base. You will work in close collaboration with a talented team of engineers, data analysts, business operations specialists, and product/marketing managers to design and deliver solutions, features, algorithms, and products powered by our rich data and state-of-the-art machine learning technology.

Responsibilities:

1. Develop and evaluate AI models for KYC fraud detection, especially in face verification and document forgery use cases.
2. Explore and prototype LLM-based solutions to automate case review, generate rule-based explanations, and assist in fraud pattern mining.
3. Utilise our petabyte-scale data warehouse to conduct in-depth analyses aimed at delivering personalised services and enabling automated detection of abnormal user behavior.
4. Collaborate with data scientists and engineers to optimize detection pipelines and provide actionable insights to stakeholders.

Requirements:

1. Able to commit for at least 6-12 months.
2. Currently enrolled as a full-time undergraduate or graduate student.
3. Hands-on experience in developing image analysis and video analysis models.
4. Strong grasp of AI concepts and mathematical foundations, including deep learning, generative AI, reinforcement learning, prompt engineering, and optimisation techniques.
5. Proficiency in programming languages such as Python; SQL is preferred.