Quant Researcher

Injective

Quant Researcher studying the crypto market and building automated trading strategies for Injective Labs. Part of a fast-paced team leveraging blockchain technology in finance.

Posted 6/29/2026full-timeRemote • New York • 🇺🇸 United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in quantitative research and analysis, with a strong foundation in statistical methods and machine learning techniques. Proficient in Python and experienced in high-frequency trading development, risk management, and performance optimization.

Highest-signal resume keywords

Quantitative Research/Analysis ExperienceExpert-Level Python ProgrammingHigh-Frequency Trading DevelopmentStatistical Analysis and BacktestingRisk Management Principles

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Statistical TechniquesMachine LearningTime-Series ModelingData StructuresAlgorithmsBacktesting MethodologiesAlgorithm DevelopmentPerformance AnalysisRisk Metrics DevelopmentTrading Signal Generation

Tools & Technologies

C++RustVersion ControlData PipelinesResearch PlatformsSignal-Generation PipelinesParameter-Optimization ToolingOrder Management SystemsExchange ConnectivityDashboards

Industry Keywords

Market MicrostructureTrading OpportunitiesMarket-Making StrategiesArbitrage StrategiesSystematic StrategiesFinancial MarketsRisk MonitoringPost-Trade AnalyticsExecution QualityMarket Impact

Tech Stack

Tools & technologies

PythonRust

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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.

Benefits

Comp & perks

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.