About the roleWe are looking for a Quantitative Researcher to fit into our existing highly-skilled NY-based quantitative team. You will report directly to the Quant Team Lead and work closely with the broader Quant team. As a part of our Quant team, you'll be studying the crypto market to find profitable trading opportunities and build automated trading strategies. The ideal candidate would be someone who has experience working with low-latency execution engines, handling real-time market data, and producing strategies that react immediately to market changes. If this sounds like you and you enjoy working in fast-paced environments, this role is for you!
Responsibilities:- Analyze market microstructure and on-chain data to identify inefficiencies and trading opportunities.
- Apply statistical and machine-learning techniques to generate, validate, and improve trading signals.
- Design and implement market-making, arbitrage, and systematic strategies end-to-end.
- Build and maintain signal-generation pipelines, feature stores, and parameter-optimization tooling.
- Develop robust backtesting frameworks; conduct performance analysis and attribution.
- Implement trading system components, including order management and exchange connectivity.
- Build and operate data pipelines and research platforms for high-quality, reproducible research.
- Ensure system reliability, scalability, and latency/performance optimization in production.
- Implement risk monitoring and control systems across strategies and venues.
- Run post-trade analytics to evaluate execution quality, slippage, and market impact.
- Develop risk metrics, dashboards, and reporting tools for strategy and portfolio oversight.
- Run simulations and estimate market impact for both liquid and illiquid assets.
Who you are:- M.S. or Ph.D. in Mathematics, Physics, Statistics, Computer Science, or a related quantitative field.
- 3-5 years of quantitative research/analysis or development experience.
- Experience in HFT development.
- Strong foundation in probability, statistics, time-series modeling, and quantitative methods.
- Expert-level Python for research and production; proficiency in C++ or Rust for performance-critical components.
- Solid grasp of data structures, algorithms, software engineering principles, and version control.
- Experience with statistical analysis, backtesting methodologies, and strategy development.
- Ability to create and use algorithms to investigate large datasets and resolve data/logic errors with rigor.
- Understanding of financial markets, trading concepts, and risk-management principles.
- Ideally based in New York or willing to relocate.
Preferred:- Experience with machine-learning frameworks and distributed/parallel computing.
- Familiarity with Linux development environments and modern DevOps practices.
- Understanding of cryptocurrency markets, DeFi protocols, and on-chain analytics.
- Experience with real-time trading systems, low-latency applications, and exchange integrations.
- Knowledge of blockchain technology, smart-contract fundamentals, and MEV-aware strategies.
- Professional certifications (e.g., CFA, FRM), prior experience in quantitative trading/fintech, and/or publications in relevant fields.
Why work with us?- Competitive salary and INJ token award.
- Unlimited PTO.
- Health Insurance.
- Equipment.
- Home Office Stipend.
- Flexible working hours.
- Opportunity to work on cutting-edge blockchain technology in the finance industry.
- Collaborative team culture with opportunities for professional growth and development.
- Global team meet ups.
