Quantitative Trading & Research – CMBS Analyst

About the role

Join the Quantitative Trading & Research team as an embedded Quantitative Strategist within the CMBS business. You will apply AI engineering, analytics, and automation across the full deal lifecycle – from origination to execution, monitoring, and reporting – while working closely with senior investment professionals.

Key responsibilities

• Develop a deep understanding of CMBS/CRE deal workflows and identify high‑impact automation opportunities.
• Design, build, and deploy ML/LLM solutions that reduce turnaround time, minimize errors, and enhance analytical insight.
• Create document‑intelligence tools to extract structured data from legal, underwriting, and acquisition materials.
• Deliver controlled draft‑generation workflows for front‑office content with human‑in‑the‑loop review.
• Build Python‑based tools and data pipelines for market monitoring, deal sourcing, scenario analysis, and portfolio performance reporting.
• Partner with technology and business stakeholders to embed solutions into origination, distribution, risk, and asset‑management systems, including third‑party data platforms.

Required profile

• Bachelor's or higher in a quantitative discipline (e.g., Computer Science, Engineering, Data Science, Finance, Real Estate).
• 3+ years of experience as a quantitative strategist, data engineer, or applying ML/LLMs to production workflows.
• Strong ability to decompose complex workflows, identify root causes, and deliver scalable improvements with minimal supervision.
• Excellent written and verbal communication skills to convey technical concepts to credit and non‑technical partners.

Required skills

• Python programming.
• Building reliable data pipelines on a centralized data warehouse.
• Working with structured and unstructured data, including vector databases.
• Fine‑tuning, evaluation frameworks, and RAG/MCP patterns for LLM integration.
• Machine learning and large language model (LLM) development.