Quantitative Researcher/Trader
6 hours ago
About Us:
We are building an in-house Asset Management & Quant Research division focused on next-generation high-frequency and quantitative trading.
Our mission is to combine:
- Quant 3.0 capabilities — multi-asset statistical strategies, factor research, systematic risk management, backtesting, and infrastructure optimization
- Quant 4.0 capabilities — AI-driven agents, reinforcement learning execution, LLM-assisted research, autonomous cross-market monitoring, and data-centric alpha discovery
We aim to leverage both traditional quantitative techniques and next-gen AI-driven methods on centralized and decentralized platforms such as Hyperliquid.
Responsibilities:
- Research, design, and implement quantitative trading strategies: market-making, arbitrage, statistical arbitrage, trend-following, execution algos.
- Conduct Quant 3.0 workflows:
-Multi-asset factor research
-Statistical modeling & backtesting
-Portfolio construction & risk management
-Systematic alpha evaluation
- Develop and optimize Quant 4.0 strategies:
-RL-based autonomous execution agents
-LLM-assisted research pipelines
-Real-time cross-market monitoring & predictive analytics
- Build low-latency infrastructure, APIs, and data pipelines to support high-frequency and on-chain trading.
- Monitor live strategies, PnL, and risk exposures, integrating both traditional and AI-driven metrics.
Requirements:
- Strong quantitative background in algorithmic trading, financial engineering, or quantitative research.
- Proficiency in Python, C++, Rust, or Golang for prototyping and low-latency execution.
- Deep understanding of market microstructure, order book dynamics, and liquidity provision.
- Familiarity with DEXs (Hyperliquid, Aster) and CEXs (Binance, OKX).
- Quant 3.0 skills:
-Time-series modeling, stochastic processes, factor research
-Multi-asset portfolio construction and risk management
-Strategy backtesting, optimization, and simulation
- Quant 4.0 skills:
-Reinforcement learning / autonomous execution
-LLM-assisted research & predictive/generative modeling
-Multi-agent market monitoring & data-centric alpha discovery
- Ability to work in a fast-paced, high-performance, research-driven environment.
Preferred Skills:
- Prior experience at a prop trading firm, HFT desk, hedge fund, or crypto quant team.
- Experience building execution engines, trading bots, or OMS/EMS pipelines.
- Hands-on experience with DEXs, AMMs, DeFi, MEV, or derivatives protocols.
- Track record of profitable strategies in crypto or traditional markets.
- Familiarity with open-source frameworks such as Hummingbot or Freqtrade.
- Experience with Quant 4.0 systems (AI-agent trading, RL-based execution, LLM research assistants) is a plus.
What We Offer:
- Competitive base salary + performance-based bonus.
- Early member of the Asset Management & Quant Research division.
- Access to premium datasets, compute resources, and research infrastructure.
- Collaborative, high-performance, research-driven team culture.
- Freedom to explore and build Quant 3.0 and Quant 4.0 strategies, from statistical alpha discovery to autonomous execution systems.
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