Pioneer Talent Program - Research Data Scientist (APAC Remote)

Binance
Template, China

Who this role is best for

A natural match if you have experience in generative AI and multi-agent systems research.

Best fit for

  • Candidates with AI research experience in financial or adversarial domains
    — “focus areas include reasoning under market uncertainty, alignment of trading agents, multi-agent coordination”
  • Researchers with a track record in LLM post-training and alignment techniques
    — “Deep understanding of transformer architectures, large language model pretraining dynamics, and post-training methodology”
  • Individuals who have published in top-tier AI/ML conferences and built core AI systems
    — “First-author publications at top-tier AI/ML conferences on LLM/Agent core topics”

Things to consider

  • Bilingual English/Mandarin is a mandatory requirement for stakeholder coordination
    — “Bilingual English/Mandarin to coordinate with overseas partners and stakeholders”
  • The role may require on-site presence depending on team and project needs
    — “Remote-first, work-from-home arrangement (may vary depending on the nature of the role and team)”

How to stand out

  • Emphasize original research contributions in financial or market uncertainty contexts
    — “Conduct original research in generative AI and large language models applied to crypto and financial domains”
  • Highlight experience in designing reward functions and training pipelines for AI agents
    — “Experience designing reward functions, training pipelines, or evaluation frameworks for LLM-based agents”
  • Demonstrate expertise in RLVR-based reasoning and test-time scaling techniques
    — “Research test-time scaling techniques — process reward models, self-consistency, Monte Carlo Tree Search-based planning”
  • Mention hands-on development experience with AI-native tools like Copilot Workspace
    — “AI-native development workflow — using tools like Claude Code, Cursor, or Copilot Workspace”
Pace · Fast PacedCollaboration · MediumAutonomy · HighDecision Impact · Industry

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • conduct original research in generative AI and large language models
  • develop novel post-training methodologies
  • research test-time scaling techniques
Typical background
Master's or PhD in Machine Learning, Computer Science, Mathematics, Statistics, or related field

Skills & requirements

Required

Machine LearningLarge Language ModelsPost-training AlignmentEfficient InferenceMulti-agent CoordinationTest-time Scaling

Preferred

First-author Publications At Top-tier Ai/ml Conferences

Stack & domain

PythonPyTorchResearchProblem-solvingCommunicationAIMachine LearningCryptocurrency

About the role

Original posting from Binance via Greenhouse

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

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

Requirements

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

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

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

Proficiency in Python and PyTorch

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

Bilingual English/Mandarin to coordinate with overseas partners and stakeholders

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

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.

By submitting a job application, you acknowledge that you have read our Candidate Privacy Notice.

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.

Source: Binance careers (Greenhouse)

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