Binance Accelerator Program - Data Scientist (Risk Management)

About Binance

Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users. We are trusted by over 230 million people in 100+ countries for our industry-leading security, user fund transparency, trading engine speed, deep liquidity, and an unmatched portfolio of digital-asset products. Binance offerings range from trading and finance to education, research, payments, institutional services, Web3 features, and more. We leverage the power of digital assets and blockchain to build an inclusive financial ecosystem to advance the freedom of money and improve financial access for people around the world.

About Binance Accelerator Program

Binance Accelerator Program is a concise fixed-term program designed for Early Career Talent to have an immersive experience in the rapidly expanding Web3 space. You will be given the opportunity to experience life at Binance and understand what goes on behind the scenes of the world’s leading blockchain ecosystem. Alongside your job, there will also be a focus on networking and development, which will expand your professional network and build transferable skills to propel you forward in your career. Learn about BAP Program HERE.

Who may apply

Current university students and recent graduates.

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.
• Utilize our petabyte-scale data warehouse to conduct in-depth analyses aimed at delivering personalized 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 optimization techniques.
• Proficiency in programming languages such as Python, SQL is preferred.