Quantitative Researcher

About Us:

Founded two decades ago and headquartered in Chicago, the DV Group of financial services firms has grown to more than 600 people across North America, Europe and Asia. Since becoming an independent proprietary trading firm in 2016, DV Trading has scaled rapidly using its own capital, strategies and risk management to provide liquidity to markets worldwide. DV Group affiliates today include two broker-dealers, a cryptocurrency market maker and a growing investment adviser.
DV Equities is the group's Asia-Pacific equities and futures market-making business, trading cash equities, ETFs, index futures and related products on exchanges across the region.

Overview:

We are looking for an experienced Quantitative Researcher to join our equities team. This role is open to candidates with hands-on experience in multi-frequency signal research across different time horizons. You will work closely with senior researchers and traders across our global offices (NYC, London, and Hong Kong) to explore market data, develop predictive signals, and build models that directly inform real trading decisions.
This is a full-cycle research role—from data exploration to production deployment, from model development to live performance monitoring—with end-to-end ownership of the research process.

Responsibilities:

• Analyze market data to uncover patterns, inefficiencies, and predictive signals across different time horizons
• Build and backtest quantitative models using historical market data
• Apply statistical and machine learning techniques—with an emphasis on tree-based methods—to enhance signal quality
• Collaborate with researchers and traders to translate research insights into production-ready strategies
• Develop and maintain data pipelines for large-scale, high-frequency, and time-series market data
• Continuously monitor and iterate on live signals and models based on performance

Requirements:

• 2+ years of professional or research experience in high-frequency research and/or longer-term signal generation
• Degree in a quantitative field (Mathematics, Statistics, Computer Science, Physics, Engineering, Financial Engineering, or related)
• Strong proficiency in Python, including standard data science libraries (pandas, NumPy, etc.)
• Genuine curiosity about financial markets and market microstructure
• Solid foundation in statistics and quantitative analysis
• Strong problem-solving skills and intellectual curiosity
• Ability to communicate technical findings clearly to both technical and non-technical audiences