
Binance Accelerator Program - Data Scientist (Risk Management)
BinancePosted 4/17/2025

Binance Accelerator Program - Data Scientist (Risk Management)
Binance
Job Location
Job Summary
The Binance Accelerator Program - Data Scientist (Risk Management) is a 6-12 month program designed for early career talent to work with the world's leading blockchain ecosystem. As a data scientist, you'll leverage vast datasets and cutting-edge machine learning infrastructure to develop AI models for KYC fraud detection, automate case review, and assist in fraud pattern mining. You'll collaborate with a talented team of engineers, data analysts, and product/marketing managers to design and deliver solutions that serve Binance's extensive global user base. With a focus on safety, scalability, and performance, this role offers opportunities for career growth, continuous learning, and autonomy in an innovative environment. By joining Binance, you'll shape the future of blockchain and contribute to building a safer, smarter crypto future. The program is open to current university students and recent graduates with hands-on experience in image analysis and video analysis models, strong AI concepts, and proficiency in programming languages such as Python and SQL.
Job Description
Responsibilities:
- Develop and evaluate AI models for KYC fraud detection, especially in face verification and document forgery use cases.
- Explore and prototype LLM-based solutions to automate case review, generate rule-based explanations, and assist in fraud pattern mining.
- Utilise our petabyte-scale data warehouse to conduct in-depth analyses aimed at delivering personalised services and enabling automated detection of abnormal user behavior.
- Collaborate with data scientists and engineers to optimize detection pipelines and provide actionable insights to stakeholders.
Requirements:
- Able to commit for at least 6-12 months.
- Currently enrolled as a full-time undergraduate or graduate student.
- Hands-on experience in developing image analysis and video analysis models.
- Strong grasp of AI concepts and mathematical foundations, including deep learning, generative AI, reinforcement learning, prompt engineering and optimisation techniques.
- Proficiency in programming languages such as Python, SQL is preferred.