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.