Binance Accelerator Program - Research Data Scientist

Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users. Binance is trusted by more than 320 million people in 100+ countries for its industry-leading security, transparency, trading engine speed, protections for investors, and unmatched portfolio of digital asset products and offerings from trading and finance to education, research, social good, payments, institutional services, and Web3 features. Binance is devoted to building an inclusive crypto ecosystem to increase the freedom of money and financial access for people around the world with crypto as the fundamental means. About Binance Accelerator Program Binance Accelerator Program (BAP) is a 3-6 month internship program designed for Early Career talent to have firsthand experience in the rapidly expanding digital assets space. You will be given the opportunity to develop your skills at Binance and understand what it’s like to work at the world's leading blockchain ecosystem. As part of your internship in the BAP, there will also be opportunities for networking and development, which will expand your professional network and build transferable skills to propel you forward in your career. Learn about the BAP Program HERE . Who may apply Current university students and recent graduates. *Terms of employment / engagement shall be subject to contract and local applicable laws About the Role For all students looking to gain hands-on experience! You'll work directly with senior scientists on research problems at the frontier of LLM reasoning, post-training methodology, and agentic AI — applied to global crypto markets. Your work has a direct path to production systems serving hundreds of millions of users, and where findings warrant it, a clear path to external publication. You run experiments, implement ideas from recent research, synthesize papers into hypotheses, and work with engineers to understand how research translates to real systems. This is not a purely literature-review or passive research role. You are expected to think independently and generate insight. 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. Responsibilities Contribute to the design and execution of experiments in reasoning model training, post-training alignment, test-time scaling, or systematic model evaluation — with a focus on applications in financial and crypto-native contexts Review and synthesize recent academic literature at NeurIPS, ICML, ICLR, and ACL — tracking developments in reasoning, alignment, and agentic AI to inform and sharpen ongoing research directions Implement model variants, training procedures including RLVR-based approaches, and evaluation protocols using PyTorch and the Hugging Face ecosystem Track and log experiments systematically using Weights & Biases or equivalent — maintaining reproducibility standards throughout Explore the intersection of LLM reasoning and crypto-native data: on-chain signals, market microstructure, multi-modal market intelligence — identifying research opportunities unique to Binance's position Collaborate with applied engineering teams to understand how research findings translate into production constraints in a zero-downtime, 24/7 trading environment Qualifications Currently pursuing a Master's or PhD in Machine Learning, Computer Science, Mathematics, or related field strongly preferred; Expected graduation in 2026, 2027, or 2028 Strong Python programming skills and PyTorch proficiency; C++ or Rust exposure a plus. Equally important: demonstrated comfort with vibe coding — using AI-assisted development tools fluidly as part of your research and experimentation workflow Solid understanding of transformer architectures, large language model pretraining, and the evolution toward reasoning models