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- Analyze high-frequency limit orderbook data to identify patterns, inefficiencies, and predictive signals
- Build and backtest quantitative models using historical tick and orderbook data
- Collaborate with senior researchers and traders to translate research findings into production-ready strategies
- Develop and maintain data pipelines for processing large-scale, high-frequency market data
- Apply statistical and machine learning techniques, particularly tree-based methods, to improve signal quality
- Continuously monitor and iterate on live signals and models based on performance
- 1-3 years of professional or research experience working directly with orderbook / limit order book (LOB) data
- Technical degree/background in a quantitative field (Math, Statistics, CS, Physics, Engineering, Financial Engineering)
- Strong proficiency in Python, including standard data science libraries (pandas, NumPy, etc.)
- Genuine interest in financial markets and market microstructure - you follow markets, not just models
- Solid foundation in statistics and quantitative analysis
- Strong problem-solving skills and intellectual curiosity
- Ability to communicate technical findings clearly to non-technical stakeholders
About DV Trading
DV Trading, founded in 2006 in Chicago as DV Group, is a proprietary trading firm active in commodities, equities and crypto via DV Chain, its institutional crypto desk providing liquidity and OTC services. With 400+ employees across Chicago, New York and London, DV combines market making, systematic strategies and venture via DV Crypto. Candidates need strong quantitative reasoning, risk discipline and interest in 24/7 crypto markets. DV Chain and DV Trading deploy proprietary quantitative algorithms and automated market making infrastructure to supply 24/7 liquidity across digital asset markets. DV Trading brings quantitative risk management and deep liquidity provisioning across spot markets, futures exchanges, and decentralized finance protocols.