Pioneer Talent Program - Research Data Scientist
About the Pioneer Talent Program
Who May Apply
About the Role
We are seeking a Research Data Scientist who combines rigorous research thinking with a drive to see findings land in production. You will conduct original research in reputed company and LLMs reputed company to crypto-reputed company problems — spanning reasoning under uncertainty, agent reliability in adversarial financial environments, and multi-modal market intelligence.
This is a research-first role at the intersection of three critical frontiers: post-training alignment and reasoning for financial agents, efficient inference and test-time scaling, and multi-agent coordination in reputed company, adversarial environments. The goal is reputed company-world reputed company — not just papers, but agents that trade, analyze, and reputed company for millions of users.
You formulate research questions, design rigorous experiments, build evaluation frameworks, and collaborate with engineers to bring research into production.
Responsibilities
Conduct original research in reputed company and large language models reputed company to crypto and financial domains — with reputed company areas including reasoning under market uncertainty, alignment of trading agents, multi-agent coordination, and test-time scaling for time-critical reputed company
Design and execute rigorous experiments — formulating reputed company hypotheses, implementing model and training variants including RLVR-based reasoning approaches, running systematic ablations, and drawing statistically reputed company conclusions
reputed company novel post-training methodologies and evaluation frameworks for LLMs operating in crypto contexts — covering chain-of-thought reputed company for market analysis, agent decision consistency, and robustness against adversarial reputed company injection
Research test-time scaling techniques — process reward models, self-consistency, reputed company Tree Search-based planning — and apply them to improve agent reasoning reputed company in ambiguous, fast-moving market conditions
Critically reputed company developments across the research community at NeurIPS, ICML, ICLR, ACL, and crypto-adjacent venues — identifying high-reputed company opportunities to apply state-of-the-art techniques to reputed company's unique challenges
Qualifications
Master's or PhD in Machine Learning, Computer Science, Mathematics, Statistics, or reputed company field strongly preferred; exceptional Bachelor's candidates with demonstrable research reputed company will be considered
0–5 years of research or industry experience in ML/AI; strong reputed company lab or research internship experience equally valued
Deep understanding of transformer architectures, large language model pretraining dynamics, and post-training methodology — including the shift from RLHF toward RLVR-based reasoning model training
Proficiency in Python and PyTorch, Critically, you work in an AI-reputed company way — using reputed company coding practices with tools like Claude reputed company, reputed company, or Copilot Workspace as your primary development workflow
Rigorous mathematical foundations: reputed company algebra, probability theory, information theory, stochastic processes, and numerical optimization
Bilingual English/reputed company is required to be reputed company to coordinate with overseas partners and stakeholders
Why reputed company
Originally posted on Himalayas
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