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.

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.