Verition Group LLC
Execution Researcher
Verition Fund Management LLC ("Verition") is a multi-strategy, multi-manager hedge fund founded in 2008. Verition focuses on global investment strategies including Global Credit, Global Convertible, Volatility & Capital Structure Arbitrage, Event-Driven Investing, Equity Long/Short & Capital Markets Trading, and Global Quantitative Trading. We are seeking a highly analytical and market-savvy researcher to join our Trading and Execution Research team as an Execution Researcher. This role focuses on optimizing execution quality through data-driven insights, leveraging internal crossing opportunities, and refining algo wheel performance. The ideal candidate has strong quantitative skills, a deep understanding of equity market microstructure, and a passion for improving trading outcomes through empirical research. Responsibilities: Analyze execution data to identify patterns, inefficiencies, and opportunities for internal crossing and broker selection. Conduct in-depth research on internalization opportunities to enhance fill rates and reduce transaction costs. Design, implement, and maintain frameworks to evaluate and optimize algo wheel performance across multiple brokers and strategies. Develop execution quality benchmarks (e.g., implementation shortfall, arrival price slippage, spread capture). Collaborate with portfolio managers, traders, and data scientists to integrate research findings into trading workflows. Evaluate broker algorithms using statistical and machine learning methods, and provide recommendations for wheel inclusion and sizing. Monitor market structure developments (e.g., exchange rule changes, ATS innovation) and assess their impact on internalization and algo efficacy. Generate periodic performance reports and research memos for senior management and trading desks. Qualifications: Advanced degree in a quantitative field such as Financial Engineering, Applied Mathematics, Statistics, or Computer Science. 3+ years of experience in trading research, preferably at a buy-side institution, broker-dealer, or exchange. Expertise in equity market microstructure, internalization practices, and algo trading. Proficiency in Python, R, or similar for data analysis and model development. Experience working with TCA (Transaction Cost Analysis) systems and execution data sets (e.g., FIX logs, OMS/EMS exports). Strong communication skills and ability to translate complex data insights into actionable strategies. Knowledge of broker algorithms, liquidity fragmentation, and smart order routing is a plus. Preferred Skills: Experience with KDB+/Q and cloud data warehouses like Redshift. Familiarity with tools like FlexTrade and Bloomberg EMSX. Demonstrated ability to influence trading decisions through quantitative analysis. Salary Range: $120,000 - $175,000 USD
Verition Fund Management LLC ("Verition") is a multi-strategy, multi-manager hedge fund founded in 2008. Verition focuses on global investment strategies including Global Credit, Global Convertible, Volatility & Capital Structure Arbitrage, Event-Driven Investing, Equity Long/Short & Capital Markets Trading, and Global Quantitative Trading. We are seeking a highly analytical and market-savvy researcher to join our Trading and Execution Research team as an Execution Researcher. This role focuses on optimizing execution quality through data-driven insights, leveraging internal crossing opportunities, and refining algo wheel performance. The ideal candidate has strong quantitative skills, a deep understanding of equity market microstructure, and a passion for improving trading outcomes through empirical research. Responsibilities: Analyze execution data to identify patterns, inefficiencies, and opportunities for internal crossing and broker selection. Conduct in-depth research on internalization opportunities to enhance fill rates and reduce transaction costs. Design, implement, and maintain frameworks to evaluate and optimize algo wheel performance across multiple brokers and strategies. Develop execution quality benchmarks (e.g., implementation shortfall, arrival price slippage, spread capture). Collaborate with portfolio managers, traders, and data scientists to integrate research findings into trading workflows. Evaluate broker algorithms using statistical and machine learning methods, and provide recommendations for wheel inclusion and sizing. Monitor market structure developments (e.g., exchange rule changes, ATS innovation) and assess their impact on internalization and algo efficacy. Generate periodic performance reports and research memos for senior management and trading desks. Qualifications: Advanced degree in a quantitative field such as Financial Engineering, Applied Mathematics, Statistics, or Computer Science. 3+ years of experience in trading research, preferably at a buy-side institution, broker-dealer, or exchange. Expertise in equity market microstructure, internalization practices, and algo trading. Proficiency in Python, R, or similar for data analysis and model development. Experience working with TCA (Transaction Cost Analysis) systems and execution data sets (e.g., FIX logs, OMS/EMS exports). Strong communication skills and ability to translate complex data insights into actionable strategies. Knowledge of broker algorithms, liquidity fragmentation, and smart order routing is a plus. Preferred Skills: Experience with KDB+/Q and cloud data warehouses like Redshift. Familiarity with tools like FlexTrade and Bloomberg EMSX. Demonstrated ability to influence trading decisions through quantitative analysis. Salary Range: $120,000 - $175,000 USD