Associate

About the Role

As an Associate in the Quantitative Trading & Research team, you will develop quantitative models, algorithms, and analytical capabilities that improve how Sales teams engage with clients. You will transform complex data into relevant signals, dynamic client content, trade ideas, and post-trade opportunities, including rolls, 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, and LLMs where they add value.

Key Responsibilities

• Research, develop, and validate models and algorithms for data processing, signal identification, opportunity prioritization, and Sales analytics.
• Construct reproducible research datasets and develop methods for extracting, enriching, and interpreting structured and unstructured data.
• Build reusable executable analytical capabilities, including tools, skills, and plugins, that encode research methods for use in Sales applications and AI-assisted workflows.
• Develop dynamic, data-derived client content grounded in analytical insights, with clear source attribution and supporting rationale, for outreach and responses to inbound requests.
• Develop algorithms to generate trade ideas and identify post-trade opportunities, including rolls, using client positions, objectives, product characteristics, and market conditions.
• Design experiments and evaluation benchmarks, compare approaches against baselines, and use error analysis and Sales feedback to improve analytical quality and business impact.
• Implement and maintain production-quality analytical code, with testing, reproducibility, explainability, and monitoring of model and output performance.
• Partner with Sales to identify valuable research problems, and with Technology, Data, and Product to integrate analytical capabilities into shared platforms, retaining ownership of methodology and analytical logic while reusing existing data services and workflow infrastructure.

Requirements & Tech Stack

• Strong Python and SQL skills, with experience developing modular, testable analytical software for production use.
• Strong quantitative foundations in probability, statistics, numerical methods, machine learning, or related disciplines.
• Experience designing, implementing, and evaluating models, algorithms, or analytical techniques against real business problems.
• Hands-on experience working with complex datasets, including data preparation, feature engineering, validation, and reproducible analysis.
• Ability to design rigorous experiments, interpret results, diagnose failure modes, and demonstrate measurable improvements.
• Ability to explain analytical methods, assumptions, and trade-offs clearly to technical and non-technical stakeholders.
• Practical judgment and ownership of research delivery, with appropriate handling of confidential data and adherence to established risk and change controls.

Qualifications

• Advanced degree in Mathematics, Statistics, Computer Science, Data Science, Physics, Engineering, Quantitative Finance, or a related field.

Preferred Qualifications

• Experience with derivatives products, client portfolios or positions, Sales analytics, or trade-lifecycle opportunities such as rolls.
• Experience analyzing financial, client-interaction, or time-series datasets to identify actionable signals.
• Experience developing recommendation or prioritization algorithms, or dynamic analytical client content with traceable sources.
• Experience applying ML or LLMs to data interpretation, retrieval, content generation, or decision support, including evaluation and monitoring.
• Experience integrating analytical code into applications or AI agents through reusable tools, skills, plugins, or MCP interfaces.