Pioneer Talent Program - Research Data Scientist

About the Role
We are seeking a Research Data Scientist who combines rigorous research thinking with a drive to see findings land in production. 
This is a research-first role at the intersection of post-training alignment & reasoning, efficient inference and test-time scaling, and multi-agent coordination in adversarial financial environments.
You will conduct original research that pushes the boundaries of what AI agents can do — reasoning under market uncertainty, coordinating with other agents in open adversarial settings, and making reliable decisions when real value is at stake. The goal is real-world impact: agents that trade, analyze, and act for millions of users across the Binance ecosystem.

Responsibilities

• Conduct original research in generative AI and large language models applied to crypto and financial domains — focus areas include reasoning under market uncertainty, alignment of trading agents, multi-agent coordination, and test-time scaling for time-critical decisions


• Design and execute rigorous experiments — formulating clear hypotheses, implementing model and training variants including RLVR-based reasoning approaches, running systematic ablations, and drawing statistically sound conclusions


• Develop novel post-training methodologies and evaluation frameworks for LLMs operating in crypto contexts — covering chain-of-thought quality for market analysis, agent decision consistency, and robustness against adversarial prompt injection


• Research test-time scaling techniques — process reward models, self-consistency, Monte Carlo Tree Search-based planning — and apply them to improve agent reasoning quality in ambiguous, fast-moving market conditions


• Critically track developments across the research community at NeurIPS, ICML, ICLR, ACL, EMNLP, and crypto-adjacent venues — identifying high-leverage opportunities to apply state-of-the-art techniques to Binance's unique challenges

Qualifications

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  Master's or PhD in Machine Learning, Computer Science, Mathematics, Statistics, or related field; exceptional Bachelor's candidates with demonstrable research output will be considered

  
  


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  0–5 years of research or industry experience in ML/AI; strong academic lab or research internship experience equally valued

  
  


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  Deep understanding of transformer architectures, large language model pretraining dynamics, and post-training methodology — including RLHF, RLVR-based reasoning model training, and alignment techniques

  
  


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  Proficiency in Python and PyTorch

  
  


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  Rigorous mathematical foundations: linear algebra, probability theory, information theory, stochastic optimization

  
  


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  Bilingual English/Mandarin to coordinate with overseas partners and stakeholders

  
  

Strongly Preferred

• First-author publications at top-tier AI/ML conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, AAAI) on LLM/Agent core topics — reasoning, multi-agent systems, RL for LLMs, post-training, agent memory, or related areas


• Research or engineering experience at a top-tier AI lab or team


• Experience designing reward functions, training pipelines, or evaluation frameworks for LLM-based agents — not just using existing APIs but building the core systems


• AI-native development workflow — using tools like Claude Code, Cursor, or Copilot Workspace as your primary development environment

• 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 enviornment 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)

Binance is committed to being an equal opportunity employer. We believe that having a diverse workforce is fundamental to our success.

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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.