Early-career Data Scientist role in Binance Accelerator Program focused on designing and evaluating AI models to detect P2P scams. Responsibilities include developing CV-based document verification, LLM-based detection and interpretable explanations, image-embedding feature extraction, and collaborating with engineers to optimize detection pipelines and deliver insights.
Binance is a leading global 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 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 worlds’ 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
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.
Requirements
- Currently enrolled as a full-time or part-time undergraduate, Master’s, or PhD student, or a recent graduate.
- Solid understanding of AI principles and mathematical foundations, including deep learning, generative AI, reinforcement learning, prompt engineering, and optimization techniques.
- Strong interest in Agentic Prompt Engineering and its applications.
Preferred Qualifications:
- Commitment to a minimum duration of 1 year.
- Proficiency in programming languages, particularly Python and SQL.
- Practical experience in developing computer vision and/or image analysis models.
Why Binance
• Shape the future with the world’s leading blockchain ecosystem
• Collaborate with world-class talent in a user-centric global organization with a flat structure
• Tackle unique, fast-paced projects with autonomy in an innovative environment
• Thrive in a results-driven workplace with opportunities for career growth and continuous learning
• Competitive salary and company benefits
• Work-from-home arrangement (the arrangement may vary depending on the work nature of the business team)
Binance is committed to being an equal opportunity employer. We believe that having a diverse workforce is fundamental to our success.
By submitting a job application, you confirm that you have read and agree to our Candidate Privacy Notice.
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