Senior Analyst CRE Finance, Data & AI

Commercial Real Estate & Structured Finance
· AI & Data Engineering

CRE / CMBS | AI Tools | Python | SQL / Postgre

SQL | Structured Finance | High Growth

We are seeking an exceptionally sharp Senior Analyst to sit at the convergence of commercial real estate finance, structured credit, and modern data infrastructure. This is not a conventional CRE role — we are building something new, and we need someone who can navigate a CMBS waterfall, write a Python pipeline, and deploy an AI workflow across a single week.

This position is designed for a high‑ceiling performer who wants real ownership, accelerated career progression, and the opportunity to shape how data, finance, and artificial intelligence intersect in the commercial real estate capital markets space. If you thrive in ambiguity, operate with precision, and move fast without breaking things, read on.

Title

Senior Analyst, CRE Finance & AI

Department

Capital Markets & Structured Finance

Type

Full‑Time

Location

Hybrid / Negotiable

Reports To

Head of Structured Finance / Managing Director

Growth Track

VP within 12–18 months

• Underwrite, model, and analyze commercial real estate loans, CMBS structures, and securitized credit products across property types (multifamily, office, industrial, retail, hospitality).
• Dissect CMBS deal documents—PSAs, offering circulars, trustee reports—and extract key credit metrics, waterfall mechanics, and covenant triggers.
• Monitor loan‑level and pool‑level performance across existing portfolios; flag credit deterioration and model stress scenarios.
• Conduct property‑level cash flow analysis, DSCR and LTV computations, and cap rate benchmarking across geographies.
• Collaborate with originators, credit teams, and rating agency liaisons to support deal execution and surveillance.
• Design, build, and maintain production‑grade Postgre
  
  SQL databases for loan tape management, deal tracking, and performance surveillance.
• Write complex SQL queries and stored procedures to support financial reporting, risk analytics, and regulatory deliverables.
• Develop Python scripts and pipelines for data ingestion, transformation, enrichment, and visualization of large structured and semi‑structured datasets.
• Integrate external CRE data feeds with internal systems to build unified data infrastructure.
• Produce automated reporting workflows that eliminate manual processes and reduce turnaround time on deliverables.

• Leverage AI and LLM‑based tools (e.g., Claude, GPT, Copilot) to accelerate document review, memo drafting, and deal summarization.
• Prototype AI‑assisted workflows for extracting structured data from loan documents, appraisals, rent rolls, and operating statements.
• Evaluate and implement emerging AI tooling that drives efficiency in credit analysis and portfolio surveillance.
• Work with engineering teams to operationalize AI models and ensure outputs meet accuracy and compliance standards.

Required

• 3–8 years of experience in commercial real estate finance, CMBS, structured credit, or a related capital markets role.
• Deep, working knowledge of CMBS structures, deal mechanics, waterfall logic, and surveillance — not just conceptual familiarity.
• Proficiency in Python: data manipulation with pandas/Num Py, automation scripting, API integrations, and basic data pipeline development.
• Strong SQL and Postgre
  
  SQL skills: query optimization, schema design, indexing, CTEs, and window functions.
• Demonstrated experience using AI tools (LLMs, copilots, or prompt engineering) to meaningfully accelerate professional work output.
• Exceptional financial modeling skills in Excel, with a track record of building robust, auditable models from scratch.
• Strong written and verbal communication skills; ability to synthesize complex data into clear, executive‑ready narratives.

Preferred

• Experience with CREFC IRP, CRED iQ, Trepp, Bloomberg, Intex, or comparable CMBS analytics platforms.
• Experience with MSCI, RCA, CoStar, Argus or other comparable CRE Data & Valuation platforms.
• Familiarity with version control (Git), REST APIs, or cloud data environments (AWS, GCP, Snowflake).
• CFA,…