Quantitative Researcher – Trading & Execution Research
Experience Level: 5–8 Years (8–10 years also considered for strong candidates)
We are working with a prestigious buy-side investment firm in New York that is seeking a Quantitative Researcher to join its Trading Research team. This is a high-impact role offering both intellectual challenge and practical influence, ideal for someone with a strong background in market microstructure, execution strategy, and quantitative signal development across equities and FX.
Responsibilities:
Influence execution outcomes by delivering innovative quantitative and systematic solutions in a collaborative team environment.
Work closely with traders and portfolio managers, integrating their insights into research and model development.
Conduct pre- and post-trade analysis to assess market impact and optimize execution across equities and FX.
Identify drivers of execution performance and contribute to improvements in counterparty selection, algorithm and venue choice, intraday trade scheduling, and market impact modeling.
Develop short-term alpha signals and forecasting models for intraday variables such as volatility, volume, and liquidity.
Lead projects from initial idea through to production, supported by a dedicated development team.
Build and improve transaction cost analysis models, enhancing the accuracy of expected cost estimates and execution strategies.
Connect themes across asset classes to produce insightful research with a liquidity and market microstructure perspective.
Contribute to team research discussions, provide mentorship to junior colleagues, and regularly present findings to internal stakeholders.
What We’re Looking For:
5–8 years of relevant experience in quantitative trading research or execution strategy (8–10 years also considered).
Demonstrated ability to build models, perform rigorous analysis, and deliver actionable insights.
Strong understanding of market microstructure, electronic trading, and algorithmic execution in global equity and FX markets.
Experience with TCA frameworks, expected cost modeling, and signal development.
Effective collaboration with both traders (low-touch and high-touch) and developers.
Proficiency in Python, R, SQL, or kdb/Q. Familiarity with machine learning applications in execution research is a plus.
Intellectual curiosity, attention to detail, and a passion for improving execution outcomes.
Strong grasp of global equity liquidity, market structure, and execution dynamics.
Reach out to quantresearch@octaviusfinance.com to apply.