About Binance Accelerator Program
Binance is a leading integral blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users. We are trusted by 300+ million people in 100+ countries for industry‑leading security, user fund transparency, trading engine speed, deep liquidity, and an unmatched portfolio of digital‑asset products. Binance offers trading, finance, education, research, payments, institutional services, Web3 features, and more. We leverage 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.
Who may apply
Current university students and recent graduates.
About the Role
As a Data Scientist on our team, you’ll be at the forefront of safeguarding Binance’s ecosystem by leveraging data to detect anomalies, assess threats, and predict potential risks across the platform. Our mission is to build intelligent, scalable systems that proactively identify fraud, prevent abuse,
and ensure the integrity of user activity without compromising on performance or user experience. Join us in building a safer, smarter crypto future.
Responsibilities
- Design, develop, and assess AI models focused on detecting P2P scams, with a particular emphasis on document verification and payment proof tampering.
- Research and prototype large language model (LLM)-based solutions to enhance automated detection, generate interpretable rule‑based explanations, and support scam pattern discovery.
- Investigate and implement cutting‑edge image embedding techniques to extract meaningful features for downstream applications such as clustering and classification.
- Collaborate closely with data scientists and engineers to optimize the detection pipeline and deliver actionable insights to key stakeholders.
Qualifications
- Currently enrolled as a full‑time or part‑time undergraduate, Master’s, or PhD student, or a recent graduate.
- Sol
📌 Binance Accelerator Program (Asia)
🏢 Binance
📍 Asia