Research Data Scientist

This is a fully remote position, open to applicants in Hong Kong.

📋 Description

• Assist in the design and implementation of experiments related to reasoning model training, post-training alignment, test-time scaling, or systematic model evaluation, particularly focusing on applications within financial and crypto-native contexts.

• Analyze and summarize recent scholarly articles from NeurIPS, ICML, ICLR, and ACL, monitoring advancements in reasoning, alignment, and agentic AI to refine and guide current research initiatives.

• Develop model variants, training methodologies including RLVR-based techniques, and evaluation frameworks utilizing PyTorch and the Hugging Face ecosystem.

• Systematically track and document experiments using Weights & Biases or similar tools, ensuring adherence to reproducibility standards throughout.

• Investigate the convergence of LLM reasoning and crypto-native data, such as on-chain signals, market microstructure, and multi-modal market intelligence, pinpointing research opportunities that are distinct to Binance's position.

• Work alongside applied engineering teams to comprehend how research insights translate into production constraints in a continuously operational, 24/7 trading environment.

⛳️ Requirements

• Currently enrolled in a Master's or PhD program in Machine Learning, Computer Science, Mathematics, or a related discipline is highly preferred.

• Anticipated graduation in 2026, 2027, or 2028.

• Proficient in Python programming and experienced with PyTorch; familiarity with C++ or Rust is advantageous. Equally crucial is a demonstrated ease with vibe coding—fluidly utilizing AI-assisted development tools as part of your research and experimentation processes.

• Solid comprehension of transformer architectures, large language model pretraining, and the progression toward reasoning models.

🏝️ Benefits

• Competitive salary and comprehensive company benefits.

• Flexible work-from-home options (specific arrangements may vary based on the business team's operational requirements).