Binance Accelerator Program - Research Data Scientist

Binance; Singapore; Remote; SGD 20,000 - 33,000; Full time

Benefits offered by this job

Remote-first

Competitive benefits

Job summary

Binance in Singapore seeks a motivated student researcher to work with senior scientists on LLM reasoning, post-training methods, and agentic AI for global crypto markets. Your work will directly contribute to experiments that may reach production systems serving hundreds of millions of users and, when warranted, publish findings.

You will run experiments, implement ideas from recent research, and translate results into practical insights with engineers, emphasizing independence and critical

Qualifications

• Currently pursuing a Master's or PhD in ML, CS, Mathematics, or related field; strongly preferred.
• Expected graduation in 2026, 2027, or 2028.
• Strong Python and PyTorch; C++ or Rust exposure a plus; vibe coding with AI-assisted tools is encouraged.
• Solid understanding of Transformer architectures and LLM pretraining; focus on reasoning models.

Responsibilities

• Design and execute 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

Skills

Python programming

PyTorch proficiency

C++ exposure

Rust exposure

Transformer architectures

Education

Master's or PhD in ML/CS/Math

Tools

Weights & Biases

Hugging Face

Job description

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, and more. Our mission is to increase the freedom of money and financial access for people around the world.

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.

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

Why Binance

• 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.