Quantitative Trading & Research Quantitative Strategist Tax Oriented Investment Associate

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 frontoffice investment workflows. This role partners closely with investment professionals to modernize deal origination underwriting and asset management through automation analytics and AIenabled 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 / LLMbased 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 proposals
  • Support scenario analysis and decisionmaking through intelligent analytics
• Design and maintain Pythonbased tools and data pipelines
  • Market intelligence and deal sourcing insights
• Portfolio pipeline and performance reporting
• Partner with technology and internal stakeholders on integrations with originations risk and P&L and asset management systems
• Rapidly prototype and iterate solutions in response to business feedback

Required qualifications capabilities and skills:

• Bachelors or advanced degree in Computer Science Engineering Data Science Mathematics or a related quantitative field
• Demonstrated expertise in ML and LLM models with a proven track record of applying to real-world business problems
• Strong programming skills (Python preferred)
• Excellent written and verbal communication skills with the ability to translate complex technical concepts for non-technical stakeholders
• Self-directed with strong critical and independent thinking abilities
• Genuine interest in financial markets and drive to apply technical skills to financial problems

Preferred qualifications capabilities and skills:

• Prior experience in deal pitching origination underwriting and investment proposals
• Familiarity with tax credit investments (e.g. affordable housing renewable energy) or related structured finance products