Quantitative Researcher
Posted 13 Jan 2026
Advertised as “Quantitative Researcher (AI Direction)”
BranchFactor Summary
The original posting with the fluff stripped out
- Management level
- Individual contributor
- Employment
- Remote
- Contract
- Full-time
No salary listed for this role.
Field of studyArtificial Intelligence, Computer Science, Mathematics, Statistics (or related)
Study levelMaster's or higher
Who We Are
Founded in 2019, Rock Bund Capital is a proprietary trading firm deeply committed to shaping the future of the cryptocurrency industry. We have an average daily trading volume reaching $1 billion and peak daily trading volume of $9 billion USD. We process over 15 million transactions daily, trading more than 1,000 symbols across major CEx and DEx. Our teams bridge traditional finance, quantitative research, and high-performance engineering with native blockchain expertise. Having mastered volatile digital asset markets, we now leverage this technical and market expertise to drive our expansion into Traditional Finance. We are inviting exceptional Ph.D. and graduates from top-tier universities to join our research team. This full-time position is designed for those eager to bridge the gap between cutting-edge academic research and real-world financial markets. You will leverage your technical skills to solve complex challenges in high-frequency trading. As an AI Researcher, you will focus on translating state-of-the-art theory into impactful trading solutions through two primary research directions:
- Deep Learning & Representation Learning: Design and train DNN architectures to create robust embeddings for complex market data.
- Alpha Generation & Strategy Optimization: Utilize AI to discover new alpha signals, enhance existing trading strategies, and drive the monetization of research into production.
Who You Are
- Ph.D. or Master’s degree in CS, AI, Math, Statistics, or a related field at a top-tier university.
- Proficient in deep learning frameworks, especially PyTorch or JAX.
- Strong coding skills in Python are required. Proficiency in C++ is a plus.
- Hands-on experience with Transformer architectures or Time-Series Foundation Models.
- Ability to read, understand, and implement state-of-the-art papers from top conferences.
- Agile problem-solver with a passion for financial technology.
- Plus: A publication record in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ACL, KDD) in relevant fields.
Why Join Us
- Competitive remuneration package and a meritocratic culture where accomplishments are rewarded
- Fast paced and result-oriented with a flat structure
- Teams collaborate in a casual working environment
- Excellent exposure to the digital asset ecosystem and the latest market insight
- Great career development opportunities