Injective Labs
Web3 Finance
QuantResearcher
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Quant Researcher at Injective Labs. Skills: Quantitative research, Automated trading, HFT development, Statistical modeling. Analyze market microstructure and on-chain data. Identify inefficiencies and trading opportunities”
Industry & Context.
Data/logic error resolution
What They're Looking For.
Must Have
M. S. or Ph. D. in Mathematics, Physics, Statistics, Computer Science, or related quantitative field, 3–5 years quantitative research/analysis or development experience, Experience in HFT development, Foundation in probability, statistics, time-series modeling, and quantitative methods, Expert-level Python for research, 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
Nice to Have
Experience with machine-learning frameworks, Experience with distributed/parallel computing, Familiarity with Linux development environments, Familiarity with modern DevOps practices, Understanding of cryptocurrency markets, Understanding of DeFi protocols, Understanding of on-chain analytics, Experience with real-time trading systems, Experience with low-latency applications, Experience with exchange integrations, Knowledge of blockchain technology, Knowledge of smart-contract fundamentals, Knowledge of MEV-aware strategies, Professional certifications, Prior experience in quantitative trading/fintech, Publications in relevant fields
What You'll Do.
Analyze market microstructure and on-chain data
Identify inefficiencies and trading opportunities
Apply statistical and machine-learning techniques
and improve trading signals
and systematic strategies
Implement market-making
and systematic strategies
Build signal-generation pipelines
Maintain signal-generation pipelines
Maintain feature stores
Build parameter-optimization tooling
Maintain parameter-optimization tooling
Develop robust backtesting
Conduct performance analysis
Conduct attribution analysis
Implement trading system components
Implement order management
Implement exchange connectivity
Operate research platforms
Ensure system reliability
Ensure latency optimization
Ensure performance optimization
Implement risk monitoring systems
Implement control systems
Run post-trade analytics
Evaluate execution quality
Evaluate market impact
Develop reporting tools
Estimate market impact
How You'll Work.
Team & Collaboration
Quantitative team
Full Job Description
ABOUT INJECTIVE LABS Injective Labs is trailblazing a new dawn for Web3 enabled finance. We are the core contributors to Injective, one of the fastest growing blockchains in the industry. Injective provides an interoperable smart contracts platform that is optimized for building decentralized finance applications. Interoperability is at the core of Injective, which is natively integrated with chains such as Ethereum, Cosmos and Solana. Developers can rapidly launch premier financial applications suited for mass adoption using Injective’s infrastructure and specialized DeFi primitives such as the world’s first fully on-chain order book. Our team has decades of experience spearheading the largest financial institutions and tech organizations. Injective is incubated by Binance and is backed by leading firms such as Jump Crypto, Pantera and Mark Cuban. ABOUT THE ROLE We are looking for a Quantitative Researcher to fit into our existing highly-skilled NY-based quantitative 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
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