Quantitative Trading & Research - Quantitative Strategist Tax Oriented Investment - Associate
JPMorgan Chase & Co.
The Tax Oriented Investments team is seeking a highly analytical and technically strong associate to apply machine learning (ML) and large language models (LLMs) to front‑office investment workflows. This role partners closely with investment professionals to modernize deal origination, underwriting, and asset management through automation, analytics, and AI‑enabled decision support. Job Summary: As an Associate on the Quantitative Trading & Research (QTR) Team, you will sit at the intersection of quantitative research, AI engineering, and front-office deal execution, offering direct exposure to senior investment professionals on complex, large-scale transactions. You will be instrumental in modernizing the deal flow through intelligent automation, data-driven insights, and the deployment of AI solutions. Job Requirements: * Develop a deep understanding of the end-to-end deal lifecycle (origination, underwriting, syndication, asset management) * Identify process inefficiencies and data gaps across deal workflows; design and implement ML / LLM‑based solutions to improve speed, accuracy, and insight * Build and deploy LLM-enabled tools to:
- Automate review of legal, underwriting, and deal documentation
- Extract structured insights from unstructured deal data
- Generate investment summaries, credit memos, and investment committee
- Support scenario analysis and decision‑making through intelligent analytics
- Design and maintain Python‑based tools and data pipelines
- Market intelligence and deal sourcing insights
- Portfolio, pipeline, and performance reporting
- Partner with technology and internal stakeholders on integrations with
- Strong programming skills (Python preferred)
- Excellent written and verbal communication skills, with the ability to
- Self-directed with strong critical and independent thinking abilities
- Genuine interest in financial markets and drive to apply technical skills to
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