Quantitative Researcher ($200k-$300k + Equity) at Injective Labs
Jack & Jill · New York, NY · 5 days ago
On-siteFinance$200k–$300k/yrFull-time
Injective Labs is a high-growth Web3 fintech incubated by Binance and backed by Jump Crypto, Pantera, and Mark Cuban, building the fastest interoperable L1 blockchain for finance.
About the role
As a Quantitative Researcher at Injective Labs, you will join a high-impact three-person team in New York to build the strategies driving the DeFi economy. You will own the entire lifecycle of automated trading strategies, from market microstructure analysis to low-latency execution, ensuring market liquidity on the world’s first fully on-chain order book.
Why this role is remarkable
- Join an elite three-person quant team where every member has end-to-end ownership, moving beyond theoretical research to ship production code with direct P&L visibility.
- Work at the absolute frontier of finance on the fastest-growing L1 blockchain, backed by industry titans like Binance, Jump Crypto, and Mark Cuban.
- Access a unique compensation structure featuring a performance-driven risk management bonus of up to $150k and INJ token equity in a scaling ecosystem.
Responsibilities
- Design and implement systematic market-making and arbitrage strategies end-to-end, utilizing statistical and machine-learning techniques to identify market inefficiencies.
- Build and maintain high-performance trading system components, including low-latency execution engines, signal-generation pipelines, and robust backtesting frameworks.
- Analyze complex on-chain data and market microstructure to optimize risk metrics, execution quality, and slippage for liquid and illiquid digital assets.
Requirements
- Holds an M.S. or Ph.D. in a quantitative field with 3–5 years of experience in HFT or systematic trading at a top-tier financial institution.
- Demonstrates expert-level proficiency in Python for research alongside strong skills in performance-critical languages like C++, Rust, or Go.
- Possesses a deep understanding of probability, time-series modeling, and financial markets, with the ability to engineer low-latency systems that react to real-time data.
Pay
$200k–$300k + equity
Location: New York, USA