[Hiring] Data Scientist @Binance

Role Description

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.

What You’ll Do

• Design, develop, and assess AI models focused on detecting P2P scams.
• Design, evaluate, and improve the agentic workflows and prompts of LLM agents in the P2P domain.
• Fine-tune smaller LLMs/VLMs (e.g. supervised fine-tuning, reinforcement learning) to improve detection accuracy and efficiency.
• 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.
• Solid understanding of AI principles and mathematical foundations, including deep learning, generative AI, reinforcement learning, prompt engineering, and optimization techniques.
• Experience in building agentic workflow and its applications.
• Strong interest in fine-tuning small LLMs or VLMs (e.g. SFT, LoRA, reinforcement learning).

Nice to Haves

• Commitment to a minimum duration of 1 year.
• Proficiency in programming languages, particularly Python and SQL.
• Practical experience with LLM applications, prompt optimization, or NLP/CV models.

Benefits

• Shape the future of finance.
• Collaborate with world-class talent in a user-centric global organization with a flat structure.
• Tackle challenging projects in a fast-paced and innovative environment with autonomy.
• Thrive in a results-driven workplace with opportunities for career growth and continuous learning.
• Competitive salary and company benefits.
• Remote-first, work-from-home arrangement (may vary depending on the nature of the role and team).