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Quantitative Trading & Research - e-Trading - Executive Director
senior · Data Science & Analytics
The Quantitative Trading & Research (QTR) eTrading team designs and delivers quantitative analytics, models, and tools that improve electronic execution outcomes for clients globally.
Job Summary
As an Executive Director in QTR eTrading, you will be aligned closely with product team, you will lead execution research and transaction cost analysis (TCA) that directly informs the electronic trading product roadmap for both single-stock and portfolio trading. You will partner with Electronic Client Solutions, Coverage, and Technology to translate research into scalable, measurable platform enhancements and client solutions.
Job Responsibilities
Product strategy & roadmap influence
Partner with Electronic Client Solutions to define and prioritize the algorithm roadmap using data-driven insights, client needs, competitive context, and measurable outcomes.
Develop a clear product analytics narrative (KPIs, benchmarks, adoption/usage, performance attribution) to support senior decision-making and investment cases.
Translate client requirements into quantitative problem statements and implementable product specifications.
Execution measurement & TCA leadership
Build, enhance, and govern TCA frameworks (benchmarks, market impact curves, peer/venue comparisons) calibrated on historical order, execution, and market data.
Diagnose execution performance drivers (order size/urgency, liquidity, volatility, venue choice, algo selection, time-of-day effects) and convert findings into product recommendations.
Establish monitoring, alerting, and post-release performance measurement for algorithm changes and new features.
Research, experimentation & model development
Conduct market microstructure research (venue structure, auctions, fee schedules, order types, dark vs. lit dynamics) and quantify the impact on execution outcomes and product design.
Design and run empirical studies and controlled experiments (A/B tests) to evaluate routing, scheduling, and parameter changes; define success metrics and ensure robust statistical conclusions.
Contribute to pre-trade and post-trade models that support strategy selection and parameterization, including regime-aware analysis where relevant.
Cross-functional delivery & stakeholder management
Collaborate with Technology and Algo Development to industrialize research into production-ready capabilities, including documentation, controls, and model/feature governance.
Create client-facing content (methodology papers, execution strategy notes, performance reviews) and support client and internal stakeholder discussions with clear, defensible analytics.
Required Qualifications, Capabilities, and Skills
Master’s degree in a STEM field (Computer Science, Engineering, Mathematics/Statistics, Physics) or equivalent practical experience.
8+ years of relevant experience in quantitative execution research, TCA, algorithmic trading, or closely related electronic trading analytics roles.
Demonstrated expertise in TCA modeling and execution quality measurement relevant to algorithmic execution strategies.
Strong programming skills in kdb+/q and Python, with experience working with large-scale trading and market datasets.
Proven ability to partner effectively with Product, Trading, and Technology to move from research findings to shipped capabilities and measurable performance improvements.
Strong analytical, quantitative, and problem-solving skills, with excellent written and verbal communication.
Preferred Qualifications, Capabilities, and Skills
PhD in a STEM field or a strong independent research track record.
10+ years of relevant experience.
Experience with stochastic control and/or numerical optimization techniques applied to single-stock and/or portfolio execution.
Experience with AWS and/or modern data processing technologies used for research-to-production workflows.
Deep knowledge of cash equities market structure and microstructure across major regions.