Quantitative Trading & Research - Cash Equities - Associate

The Quantitative Trading & Research team develops quantitative models, algorithms, analytical capabilities and agentic workflows to help Cash Equities Sales teams engage more effectively with clients.

By transforming complex client flow and transaction data, including trades, orders, axes and IOIs, into actionable signals, client-targeting insights, "who to call" recommendations, dynamic client content, trade ideas and post-trade opportunities, the team supports both inbound and outbound client workflows

Job Summary
As an Associate in the Quantitative Trading & Research team, you will develop quantitative models, algorithms, analytical capabilities and agentic workflows that improve how Cash Equities Sales teams engage with clients.

You will transform complex data, including client flow and transactional data such as trades, orders, axes and IOIs, into relevant signals, client targeting and \"who to call\" recommendations, LLM-generated dynamic client content, trade ideas and post-trade opportunities, supporting inbound and outbound client workflows.

You will own the research lifecycle from problem framing and data preparation through methodology, evaluation, production implementation and monitoring, partnering with Technology, Data and Product on integration.

You will use statistical methods, ML, LLMs and AI agents where they add value.

Job Responsibilities


* Research, develop and validate models and algorithms for data processing, signal identification, client targeting, opportunity prioritization and Sales analytics.


* Construct reproducible research datasets and develop methods for extracting, enriching and interpreting structured and unstructured data, including Cash Equities flow and transactional data (executions, orders, axes, IOIs, blocks).


* Analyze client trading behavior, including flow patterns, sector and stock preferences, position changes, liquidity needs and trading style, to identify which clients to target, with which ideas, and when.


* Develop \"who to call\" recommendation models that rank clients for Sales coverage by combining flow signals, axes and liquidity, trade ideas and market events, with a clear rationale for each recommendation.


* Build reusable executable analytical capabilities, including tools, skills and plugins, that encode research methods for use in Sales applications and AI-assisted workflows.


* Design, build and evaluate agentic workflows that orchestrate these tools, data services and models to automate multi-step Sales tasks, such as client pre-call briefings, flow summaries, idea-to-client matching and inbound request handling, with appropriate guardrails, human-in-the-loop review and auditability.


* Develop dynamic, data-derived client content grounded in analytical insights, with clear source attribution and supporting rationale, for outreach and responses to inbound requests.


* Use LLMs to generate personalized client content, such as talking points, flow ...