Quant Developer

Summary

The Quant Developer will serve as a critical bridge between quantitative researchers and engineering teams. This role focuses on turning research prototypes into reliable, scalable tools that support investment research, portfolio construction, and automation initiatives.

Ideal candidates bring strong engineering fundamentals, familiarity with quantitative methods, and comfort working in a front-office–embedded environment. This is a hands-on role with direct exposure to investment teams, requiring the ability to iterate quickly, integrate diverse datasets, and enhance model robustness.

Responsibilities

• Transform research concepts and prototypes into stable, production-ready tools, analytics, and workflows.
• Build and maintain pipelines that support AI-enhanced research, pricing analytics, tagging systems, and multi-source data ingestion.
• Collaborate with quantitative researchers to refine models, improve performance, and ensure production readiness.
• Work closely with Data Engineers and UI/UX developers to integrate model outputs into downstream systems and user-facing applications.
• Support buildout of analytics and tools involving live pricing feeds, internal tagging frameworks, economic or earnings report processing, and security-level insights.
• Evaluate existing research tools and prototypes to assess scalability, technical feasibility, and necessary enhancements for structured deployment.
• Ensure that all models and workflows meet appropriate engineering standards for reliability, auditability, and maintainability.

Requirements

• Strong Python development skills, including experience with numerical and scientific computing libraries.
• Deep SQL expertise and hands-on experience with Snowflake or similar cloud data platforms.
• Experience integrating APIs, structured and unstructured datasets, and real-time or near-real-time data sources.
• Familiarity with modern AI/ML techniques; particularly NLP, embeddings, and LLM-assisted research, is preferred.
• Experience with Domino or willingness to adapt quickly to a collaborative model development environment.
• Prior exposure to quantitative finance concepts and investment data structures (securities, pricing, holdings, benchmarks, exposures) is strongly preferred.
• Ability to act as a technical liaison with front-office quant and research teams.
• Strong communication skills and an ability to work effectively with on-desk stakeholders in a dynamic, fast-paced setting.